FaVOS v1.1.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.avro filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mds filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text

Annotations.zip

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+size 81461764

CITATION.bib

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+@inproceedings{hong2026favos,
+  title     = {When Predicting Nothing Beats SAM 3: Revisiting Evaluation in Video Object Segmentation},
+  author    = {Hong, Jihwan and Park, Woohyeon and Kim, Jaeik and Do, Jaeyoung},
+  booktitle = {Advances in Neural Information Processing Systems},
+  year      = {2026},
+  note      = {Evaluations \& Datasets Track}
+}

JPEGImages.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:56077e69e1b0c27c3d5439732b69ce5e9fe8cd801c04fe40cc8cdc1ed7384171
+size 5018261297

LICENSE.md

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+# License and source terms
+
+FaVOS 1.1.0, prepared 2026-11-06.
+
+Copyright 2026 Jihwan Hong, Woohyeon Park, Jaeik Kim, and Jaeyoung Do, AIDAS Laboratory, Seoul National University, for their newly created contributions.
+
+The authors' newly collected videos (67 videos) and segmentation annotations are licensed under the [Creative Commons Attribution-NonCommercial 4.0 International license](https://creativecommons.org/licenses/by-nc/4.0/). The [full legal code](https://creativecommons.org/licenses/by-nc/4.0/legalcode) governs these assets. Give appropriate credit, provide the license link, indicate changes, and observe the non-commercial condition.
+
+Extracted JPEG frames from the 133 YFCC100M source videos retain their respective original media licenses and source terms. They are not relicensed under the authors' CC BY-NC 4.0 license. This follows the paper's appendix, “License and Terms of Use.” The dataset-level CC BY-NC 4.0 metadata must be read with this asset-specific qualification.
+
+The [Multimedia Commons YFCC100M documentation](https://multimediacommons.wordpress.com/yfcc100m-core-dataset/) distinguishes the Webscope agreement for the metadata from the individual Creative Commons licenses for the media. A general YFCC100M label does not establish a particular video's license. Requirements may include original attribution, non-commercial conditions, ShareAlike, or restrictions on derivatives, depending on the source license.
+
+[source_provenance.csv](source_provenance.csv) identifies the source family for all 200 videos and the media hashes for the 133 YFCC videos. The available inputs do not include their original creator attributions, Flickr page URLs, or individual license URLs. Those must be recovered and checked by the authors before they can establish complete redistribution permissions, including whether extraction or face defacing complies with any ShareAlike or NoDerivatives conditions. No assertion of blanket license compatibility is made here.
+
+This release changes label IDs 2 and 3 to background in the prompt mask of video `56a8974858d46772b14884c3b3818acc`; remaining IDs are preserved. No source JPEG frame is changed relative to the review release.
+
+For source rights or dataset questions, contact Jihwan Hong at [csjihwanh@snu.ac.kr](mailto:csjihwanh@snu.ac.kr). Privacy, publicity and other rights may still apply to visual content.

README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+- image-segmentation
+tags:
+- video-object-segmentation
+- video-segmentation
+- evaluation
+- croissant
+- neurips-2026
+- video
+pretty_name: FaVOS
+size_categories:
+- 10K<n<100K
+---
+
+# FaVOS
+
+[Project page](https://aidaslab.github.io/FaVOS) | [Paper](https://arxiv.org/abs/2610.02946)
+
+FaVOS is a video object segmentation benchmark with fractional temporal visibility. It contains 200 videos and 279 annotated objects that may disappear and reappear.
+
+| Subset | Videos | Objects | Mean τ |
+|---|---:|---:|---:|
+| FaVOS-20 | 100 | 129 | 0.2051 |
+| FaVOS-40 | 100 | 150 | 0.4048 |
+| Full | 200 | 279 | 0.3124 |
+
+FaVOS evaluation uses the first annotated frame as the prompt frame. Metrics are
+computed on the remaining frames only.
+
+Download the dataset:
+
+```bash
+huggingface-cli download snu-aidas/FaVOS --repo-type dataset --local-dir data
+unzip data/JPEGImages.zip -d data
+unzip data/Annotations.zip -d data
+```
+
+Evaluate predictions against:
+
+```text
+data/Annotations/<video_id>/<frame>.png
+```
+
+Use `favos-20.txt` and `favos-40.txt` as the evaluation splits. To compute Volumetric J&F with [eval_jnf_v.py](eval_jnf_v.py):
+
+```bash
+python data/eval_jnf_v.py --pred-root predictions --output-dir results/jf_v
+```
+
+## License
+
+The annotations and the 67 self-collected videos are released under CC BY-NC 4.0. Frames from the 133 YFCC100M videos keep their original licenses. See [LICENSE.md](LICENSE.md).
+
+Contact: csjihwanh@snu.ac.kr
+
+## Citation
+
+```bibtex
+@inproceedings{hong2026favos,
+  title     = {When Predicting Nothing Beats SAM 3: Revisiting Evaluation in Video Object Segmentation},
+  author    = {Hong, Jihwan and Park, Woohyeon and Kim, Jaeik and Do, Jaeyoung},
+  booktitle = {Advances in Neural Information Processing Systems},
+  year      = {2026},
+  note      = {Evaluations \& Datasets Track}
+}
+```

SHA256SUMS

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+a2501bccf74a54d97133616ff3a598d9919639100e73ac71b9ad27b8c85fa15d  README.md
+abb18bbd04c931dc434f962cf535053c3dbf039c81654d0f40864f5bab0246f0  source_provenance.csv

eval_jnf_v.py

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+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+import os
+from concurrent.futures import ProcessPoolExecutor, as_completed
+from dataclasses import asdict, dataclass
+from pathlib import Path
+
+import numpy as np
+from PIL import Image
+from scipy.ndimage import distance_transform_edt
+from tqdm.auto import tqdm
+
+
+DATASET_ROOT = Path("data")
+SPLITS = ("favos-20", "favos-40")
+OUTPUT_DIR = Path("results/jf_v")
+BOUND_TH = 0.008
+WORKERS = min(8, os.cpu_count() or 1)
+
+
+@dataclass(frozen=True)
+class JNFVResult:
+    j_v: float
+    f_v: float
+    jnf_v: float
+    precision_v: float
+    recall_v: float
+    intersection_volume: int
+    union_volume: int
+    pred_boundary_voxels: int
+    gt_boundary_voxels: int
+
+
+@dataclass(frozen=True)
+class ObjectResult:
+    split: str
+    video_id: str
+    object_id: int
+    num_frames: int
+    j_v: float
+    f_v: float
+    jnf_v: float
+    precision_v: float
+    recall_v: float
+    intersection_volume: int
+    union_volume: int
+    pred_boundary_voxels: int
+    gt_boundary_voxels: int
+
+
+@dataclass(frozen=True)
+class VideoResult:
+    split: str
+    video_id: str
+    num_objects: int
+    num_frames: int
+    j_v: float
+    f_v: float
+    jnf_v: float
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        description=(
+            "Evaluate J&F_v on FaVOS indexed-PNG predictions. "
+            "The dataset is expected under data/."
+        )
+    )
+    parser.add_argument(
+        "--pred-root",
+        type=Path,
+        required=True,
+        help="Prediction root. Accepts either <root>/Annotations/<video_id> or <root>/<video_id>.",
+    )
+    parser.add_argument("--output-dir", type=Path, default=OUTPUT_DIR)
+    return parser.parse_args()
+
+
+def numeric_pngs(path: Path) -> list[Path]:
+    return sorted(
+        [p for p in path.glob("*.png") if p.is_file() and not p.name.startswith("._")],
+        key=lambda p: int(p.stem),
+    )
+
+
+def load_label(path: Path) -> np.ndarray:
+    with Image.open(path) as image:
+        return np.asarray(image, dtype=np.uint8)
+
+
+def read_split(dataset_root: Path, split: str) -> list[str]:
+    path = dataset_root / f"{split}.txt"
+    if not path.is_file():
+        raise FileNotFoundError(f"Missing split file: {path}")
+    ids = [line.strip() for line in path.read_text(encoding="utf-8").splitlines()]
+    return list(dict.fromkeys(video_id for video_id in ids if video_id and not video_id.startswith("#")))
+
+
+def resolve_pred_root(pred_root: Path) -> Path:
+    annotations = pred_root / "Annotations"
+    return annotations if annotations.is_dir() else pred_root
+
+
+def load_video(gt_dir: Path, pred_dir: Path) -> tuple[np.ndarray, np.ndarray]:
+    gt_paths = numeric_pngs(gt_dir)
+    pred_by_name = {p.name: p for p in numeric_pngs(pred_dir)}
+    if not gt_paths:
+        raise FileNotFoundError(f"No GT masks found in {gt_dir}")
+
+    missing = [p.name for p in gt_paths if p.name not in pred_by_name]
+    if missing:
+        raise FileNotFoundError(f"Missing {len(missing)} prediction masks in {pred_dir}: {missing[:5]}")
+
+    gt_paths = gt_paths[1:]
+    if not gt_paths:
+        raise ValueError(f"No evaluation frames found in {gt_dir}")
+
+    gt = np.stack([load_label(path) for path in gt_paths], axis=0)
+    pred = np.stack([load_label(pred_by_name[path.name]) for path in gt_paths], axis=0)
+    if gt.shape != pred.shape:
+        raise ValueError(f"Shape mismatch for {gt_dir.name}: GT {gt.shape}, pred {pred.shape}")
+    return gt, pred
+
+
+def as_bool_volume(volume: np.ndarray) -> np.ndarray:
+    if volume.ndim != 3:
+        raise ValueError(f"Expected (T,H,W), got {volume.shape}")
+    return volume.astype(bool)
+
+
+def mean_visible_area(volume: np.ndarray) -> float:
+    areas = np.sum(volume, axis=(1, 2), dtype=np.int64)
+    visible = areas[areas > 0]
+    return float(np.mean(visible)) if visible.size else 0.0
+
+
+def spatial_radius(shape_2d: tuple[int, int], object_area: float, bound_th: float) -> int:
+    radius = bound_th if bound_th >= 1 else bound_th * np.linalg.norm(shape_2d)
+    if object_area > 0:
+        radius = min(radius, 0.1 * np.sqrt(object_area))
+    return max(int(np.ceil(radius)), 0)
+
+
+def boundary_volume(volume: np.ndarray) -> np.ndarray:
+    volume = volume.astype(bool)
+    boundary = np.zeros_like(volume, dtype=bool)
+    for dt in (0, 1):
+        for dy in (0, 1):
+            for dx in (0, 1):
+                if dt == 0 and dy == 0 and dx == 0:
+                    continue
+                src = (
+                    slice(0, volume.shape[0] - dt),
+                    slice(0, volume.shape[1] - dy),
+                    slice(0, volume.shape[2] - dx),
+                )
+                dst = (
+                    slice(dt, volume.shape[0]),
+                    slice(dy, volume.shape[1]),
+                    slice(dx, volume.shape[2]),
+                )
+                boundary[src] |= volume[src] ^ volume[dst]
+    return boundary
+
+
+def count_matches(source_boundary: np.ndarray, target_boundaries: np.ndarray, radius: int) -> int:
+    if not np.any(source_boundary) or not np.any(target_boundaries):
+        return 0
+    matched = np.zeros_like(source_boundary, dtype=bool)
+    for target in target_boundaries:
+        if np.any(target):
+            matched |= distance_transform_edt(~target) <= radius
+    return int(np.sum(source_boundary & matched))
+
+
+def compute_jnf_v(
+    gt_volume: np.ndarray,
+    pred_volume: np.ndarray,
+) -> JNFVResult:
+    gt = as_bool_volume(gt_volume)
+    pred = as_bool_volume(pred_volume)
+    if gt.shape != pred.shape:
+        raise ValueError(f"Shape mismatch: GT {gt.shape}, pred {pred.shape}")
+
+    intersections = np.sum(gt & pred, axis=(1, 2), dtype=np.int64)
+    unions = np.sum(gt | pred, axis=(1, 2), dtype=np.int64)
+    total_intersection = int(np.sum(intersections, dtype=np.int64))
+    total_union = int(np.sum(unions, dtype=np.int64))
+    if total_union == 0:
+        j_v = 1.0
+    else:
+        nonempty = unions > 0
+        j_v = float(np.sum((unions[nonempty] / total_union) * (intersections[nonempty] / unions[nonempty])))
+
+    radius = spatial_radius(gt.shape[1:], mean_visible_area(gt), BOUND_TH)
+    gt_boundary = boundary_volume(gt)
+    pred_boundary = boundary_volume(pred)
+
+    matched_pred = 0
+    matched_gt = 0
+    total_pred_boundary = 0
+    total_gt_boundary = 0
+    for t in range(gt.shape[0]):
+        gt_t = gt_boundary[t]
+        pred_t = pred_boundary[t]
+        n_gt = int(np.sum(gt_t))
+        n_pred = int(np.sum(pred_t))
+        total_gt_boundary += n_gt
+        total_pred_boundary += n_pred
+        if n_gt:
+            matched_gt += count_matches(gt_t, pred_boundary[t : t + 1], radius)
+        if n_pred:
+            matched_pred += count_matches(pred_t, gt_boundary[t : t + 1], radius)
+
+    if total_pred_boundary == 0 and total_gt_boundary == 0:
+        precision = 1.0
+        recall = 1.0
+    elif total_pred_boundary == 0:
+        precision = 1.0
+        recall = 0.0
+    elif total_gt_boundary == 0:
+        precision = 0.0
+        recall = 1.0
+    else:
+        precision = float(matched_pred / total_pred_boundary)
+        recall = float(matched_gt / total_gt_boundary)
+    f_v = 0.0 if precision + recall == 0 else float(2.0 * precision * recall / (precision + recall))
+
+    return JNFVResult(
+        j_v=j_v,
+        f_v=f_v,
+        jnf_v=(j_v + f_v) / 2.0,
+        precision_v=precision,
+        recall_v=recall,
+        intersection_volume=total_intersection,
+        union_volume=total_union,
+        pred_boundary_voxels=total_pred_boundary,
+        gt_boundary_voxels=total_gt_boundary,
+    )
+
+
+def evaluate_video(task: tuple[str, Path, Path]) -> dict[str, object]:
+    video_id, gt_root, pred_root = task
+    try:
+        gt, pred = load_video(gt_root / video_id, pred_root / video_id)
+        object_ids = [int(v) for v in np.unique(gt) if int(v) != 0]
+        if not object_ids:
+            raise ValueError(f"No foreground objects in {gt_root / video_id}")
+
+        objects: list[ObjectResult] = []
+        for object_id in object_ids:
+            pred_obj = pred == object_id
+            result = compute_jnf_v(
+                gt == object_id,
+                pred_obj,
+            )
+            objects.append(
+                ObjectResult(
+                    split="all",
+                    video_id=video_id,
+                    object_id=object_id,
+                    num_frames=int(gt.shape[0]),
+                    **asdict(result),
+                )
+            )
+
+        video = VideoResult(
+            split="all",
+            video_id=video_id,
+            num_objects=len(objects),
+            num_frames=int(gt.shape[0]),
+            j_v=float(np.mean([row.j_v for row in objects])),
+            f_v=float(np.mean([row.f_v for row in objects])),
+            jnf_v=float(np.mean([row.jnf_v for row in objects])),
+        )
+        return {"video_id": video_id, "objects": objects, "video": video, "error": None}
+    except Exception as exc:
+        return {"video_id": video_id, "objects": [], "video": None, "error": {"video_id": video_id, "error": str(exc)}}
+
+
+def write_csv(path: Path, rows: list[dict[str, object]]) -> None:
+    if not rows:
+        return
+    path.parent.mkdir(parents=True, exist_ok=True)
+    with path.open("w", newline="", encoding="utf-8") as handle:
+        writer = csv.DictWriter(handle, fieldnames=list(rows[0].keys()))
+        writer.writeheader()
+        writer.writerows(rows)
+
+
+def summarize(split: str, objects: list[ObjectResult], videos: list[VideoResult]) -> dict[str, object]:
+    return {
+        "split": split,
+        "num_videos": len(videos),
+        "num_objects": len(objects),
+        "num_object_frames": int(sum(row.num_frames for row in objects)),
+        "j_v": float(np.mean([row.j_v for row in objects])) if objects else 0.0,
+        "f_v": float(np.mean([row.f_v for row in objects])) if objects else 0.0,
+        "jnf_v": float(np.mean([row.jnf_v for row in objects])) if objects else 0.0,
+        "per_video_j_v": float(np.mean([row.j_v for row in videos])) if videos else 0.0,
+        "per_video_f_v": float(np.mean([row.f_v for row in videos])) if videos else 0.0,
+        "per_video_jnf_v": float(np.mean([row.jnf_v for row in videos])) if videos else 0.0,
+    }
+
+
+def main() -> int:
+    args = parse_args()
+    dataset_root = DATASET_ROOT
+    gt_root = dataset_root / "Annotations"
+    pred_root = resolve_pred_root(args.pred_root)
+    if not gt_root.is_dir():
+        raise FileNotFoundError(f"Missing GT root: {gt_root}")
+    if not pred_root.is_dir():
+        raise FileNotFoundError(f"Missing prediction root: {pred_root}")
+
+    splits = {split: read_split(dataset_root, split) for split in SPLITS}
+    unique_ids = sorted({video_id for ids in splits.values() for video_id in ids})
+    if not unique_ids:
+        raise ValueError("No videos selected for evaluation.")
+
+    tasks = [
+        (
+            video_id,
+            gt_root,
+            pred_root,
+        )
+        for video_id in unique_ids
+    ]
+
+    objects_by_video: dict[str, list[ObjectResult]] = {}
+    videos_by_video: dict[str, VideoResult] = {}
+    max_workers = min(max(WORKERS, 1), len(tasks))
+
+    if max_workers == 1:
+        iterator = tqdm(tasks, desc="Evaluating", unit="video")
+        for task in iterator:
+            result = evaluate_video(task)
+            if result["error"] is not None:
+                raise RuntimeError(f"Failed evaluating {result['video_id']}: {result['error']['error']}")
+            objects_by_video[result["video_id"]] = result["objects"]
+            videos_by_video[result["video_id"]] = result["video"]
+    else:
+        with ProcessPoolExecutor(max_workers=max_workers) as executor:
+            futures = [executor.submit(evaluate_video, task) for task in tasks]
+            iterator = as_completed(futures)
+            iterator = tqdm(iterator, total=len(futures), desc="Evaluating", unit="video")
+            for future in iterator:
+                result = future.result()
+                if result["error"] is not None:
+                    raise RuntimeError(f"Failed evaluating {result['video_id']}: {result['error']['error']}")
+                objects_by_video[result["video_id"]] = result["objects"]
+                videos_by_video[result["video_id"]] = result["video"]
+
+    all_objects: list[ObjectResult] = []
+    all_videos: list[VideoResult] = []
+    summaries: dict[str, dict[str, object]] = {}
+    for split, ids in splits.items():
+        split_objects: list[ObjectResult] = []
+        split_videos: list[VideoResult] = []
+        for video_id in ids:
+            for row in objects_by_video.get(video_id, []):
+                split_objects.append(ObjectResult(split=split, **{k: v for k, v in asdict(row).items() if k != "split"}))
+            if video_id in videos_by_video:
+                row = videos_by_video[video_id]
+                split_videos.append(VideoResult(split=split, **{k: v for k, v in asdict(row).items() if k != "split"}))
+        all_objects.extend(split_objects)
+        all_videos.extend(split_videos)
+        summaries[split] = summarize(split, split_objects, split_videos)
+
+    args.output_dir.mkdir(parents=True, exist_ok=True)
+    write_csv(args.output_dir / "per_object_jf_v.csv", [asdict(row) for row in all_objects])
+    write_csv(args.output_dir / "per_video_jf_v.csv", [asdict(row) for row in all_videos])
+    summary = {
+        "splits": summaries,
+    }
+    (args.output_dir / "summary.json").write_text(json.dumps(summary, indent=2, sort_keys=True) + "\n", encoding="utf-8")
+
+    for split, row in summaries.items():
+        print(
+            f"{split}: videos={row['num_videos']} objects={row['num_objects']} "
+            f"Jv={row['j_v']:.6f} Fv={row['f_v']:.6f} J&F_v={row['jnf_v']:.6f}"
+        )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

favos-20.txt

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favos-40.txt

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metadata.json

@@ -0,0 +1,1119 @@
+{
+  "@context": {
+    "@language": "en",
+    "@vocab": "https://schema.org/",
+    "sc": "https://schema.org/",
+    "cr": "http://mlcommons.org/croissant/",
+    "dct": "http://purl.org/dc/terms/",
+    "prov": "http://www.w3.org/ns/prov#",
+    "citeAs": "cr:citeAs",
+    "column": "cr:column",
+    "conformsTo": "dct:conformsTo",
+    "data": {
+      "@id": "cr:data",
+      "@type": "@json"
+    },
+    "fileObject": "cr:fileObject",
+    "fileSet": "cr:fileSet",
+    "field": "cr:field",
+    "dataType": {
+      "@id": "cr:dataType",
+      "@type": "@vocab"
+    },
+    "examples": {
+      "@id": "cr:examples",
+      "@type": "@json"
+    },
+    "source": "cr:source",
+    "extract": "cr:extract",
+    "fileProperty": "cr:fileProperty",
+    "format": "cr:format",
+    "includes": "cr:includes",
+    "isLiveDataset": "cr:isLiveDataset",
+    "jsonPath": "cr:jsonPath",
+    "key": "cr:key",
+    "md5": "cr:md5",
+    "parentField": "cr:parentField",
+    "path": "cr:path",
+    "rai": "http://mlcommons.org/croissant/RAI/",
+    "recordSet": "cr:recordSet",
+    "references": "cr:references",
+    "regex": "cr:regex",
+    "repeated": "cr:repeated",
+    "replace": "cr:replace",
+    "separator": "cr:separator",
+    "subField": "cr:subField",
+    "transform": "cr:transform",
+    "equivalentProperty": "cr:equivalentProperty",
+    "samplingRate": "cr:samplingRate"
+  },
+  "@type": "sc:Dataset",
+  "name": "FaVOS",
+  "conformsTo": "http://mlcommons.org/croissant/1.1",
+  "citeAs": "@inproceedings{hong2026favos,\n  title     = {When Predicting Nothing Beats SAM 3: Revisiting Evaluation in Video Object Segmentation},\n  author    = {Hong, Jihwan and Park, Woohyeon and Kim, Jaeik and Do, Jaeyoung},\n  booktitle = {Advances in Neural Information Processing Systems},\n  year      = {2026},\n  note      = {Evaluations \\& Datasets Track}\n}",
+  "description": "FaVOS is a video object segmentation evaluation dataset with JPEG video frames, indexed PNG annotations, and two public evaluation split files.",
+  "url": "https://huggingface.co/datasets/snu-aidas/FaVOS",
+  "sameAs": "https://huggingface.co/datasets/snu-aidas/FaVOS/tree/main",
+  "license": "https://creativecommons.org/licenses/by-nc/4.0/",
+  "version": "1.1.0",
+  "datePublished": "2026-11-06",
+  "keywords": [
+    "video object segmentation",
+    "video segmentation",
+    "object masks",
+    "evaluation"
+  ],
+  "measurementTechnique": "The first annotated frame is used as the prompt frame. Evaluation metrics are computed on the remaining frames.",
+  "rai:dataLimitations": "FaVOS is intended for evaluation of prompt-based video object segmentation on selected natural videos with temporally visible objects. It is not intended to represent all video domains, camera types, geographies, object categories, demographic groups, or deployment settings. The dataset contains 200 videos and 279 object instances, so conclusions should be interpreted as benchmark evidence rather than broad real-world performance guarantees. It is not recommended for training general-purpose recognition systems, identifying people, surveillance, biometric analysis, demographic inference, or safety-critical decision making.",
+  "rai:dataBiases": "The videos were selected through source availability, quality checks, object visibility criteria, and human acceptance decisions, which can introduce selection bias toward videos with annotatable objects and sufficient visual quality. Crowded and uncrowded subsets were intentionally curated, so the distribution of object density, motion, occlusion, background, geography, culture, and human presence may differ from open-world video data. Labels are object masks produced through an iterative annotation workflow and may contain boundary errors, missed objects, or temporal inconsistencies that can affect measured model behavior.",
+  "rai:personalSensitiveInformation": "The dataset may contain the following categories of personal or sensitive information in visual form: Geography and location-related contextual cues, Culture-related contextual cues, and Others, including faces, bodies, license plates, and public-scene identifiers that may appear incidentally in source videos. The dataset does not provide identity, demographic, biometric, health, political, religious, or socio-economic labels. The released task labels are object segmentation masks, not demographic or identity annotations. Face and license-plate defacing tooling was used during preprocessing where applicable, but automated anonymization may be imperfect. The dataset should not be used to identify, track, profile, or infer sensitive attributes of people.",
+  "rai:dataUseCases": "FaVOS is designed to measure video object segmentation performance when the first annotated frame is provided as the prompt and all subsequent annotated frames are evaluated. Validated use cases include benchmarking segmentation mask quality, temporal robustness, and split-level comparisons using the provided favos-20 and favos-40 evaluation files. Validity has not been established for model training, demographic or fairness auditing, human identification, action recognition, object detection outside the annotated masks, medical or safety-critical applications, or deployment performance prediction in unrelated video domains.",
+  "rai:dataSocialImpact": "Potential positive impacts include more reproducible evaluation of video object segmentation systems and clearer measurement of segmentation quality over time. Potential negative impacts include overgeneralizing results beyond the curated benchmark, using masks to support surveillance or tracking applications, or exposing residual personal or location information in source frames. Mitigations include non-commercial licensing, hashed/remapped video identifiers, release of evaluation-only splits, documented provenance, and automated defacing of detected sensitive visual regions where applicable.",
+  "rai:hasSyntheticData": false,
+  "prov:wasDerivedFrom": [
+    {
+      "@id": "http://projects.dfki.uni-kl.de/yfcc100m/",
+      "prov:label": "YFCC100M",
+      "description": "A subset of videos was selected from YFCC100M-backed media after filtering, curation, and annotation. Source media retain their original licensing constraints."
+    },
+    {
+      "@id": "self_collected_videos",
+      "prov:label": "Self-collected video collection",
+      "description": "Additional locally collected videos were included to complement YFCC100M with scenarios relevant to low-temporal-visibility video object segmentation."
+    }
+  ],
+  "prov:wasGeneratedBy": [
+    {
+      "@type": "prov:Activity",
+      "name": "Data collection and source selection",
+      "description": "Accepted records were collected from crowded, uncrowded, and myvideo annotation stores. Crowded and uncrowded records use YFCC100M-backed video paths; myvideo records use a local video collection. Source videos were included only when the corresponding source video, JPEG frame directory, and annotation directory were present."
+    },
+    {
+      "@type": "prov:Activity",
+      "name": "Preprocessing",
+      "description": "The collection script remapped original video IDs to hashed identifiers, copied JPEG frames and indexed PNG annotations, optionally started each sequence at the stored prompt frame, renumbered frames from 00000, copied source videos for provenance, wrote name mappings and summary metadata, and packaged JPEGImages.zip, Annotations.zip, favos-20.txt, and favos-40.txt."
+    },
+    {
+      "@type": "prov:Activity",
+      "name": "Annotation",
+      "description": "Object masks were produced through an iterative video object segmentation annotation workflow using prompt frames, propagated masks, refinement prompts, and human accept/reject review. The released indexed PNG masks encode object instances for evaluation."
+    },
+    {
+      "@type": "prov:Activity",
+      "name": "Sensitive-region mitigation",
+      "description": "Preprocessing included automated defacing scripts for detected human faces and license plates where applicable, including InsightFace SCRFD-based face detection and optional YOLO-based restoration/defacing workflows."
+    }
+  ],
+  "additionalProperty": [
+    {
+      "@type": "PropertyValue",
+      "name": "num_videos",
+      "value": 200
+    },
+    {
+      "@type": "PropertyValue",
+      "name": "num_frames",
+      "value": 39422
+    },
+    {
+      "@type": "PropertyValue",
+      "name": "num_object_instances",
+      "value": 279
+    },
+    {
+      "@type": "PropertyValue",
+      "name": "frame_count_min",
+      "value": 55
+    },
+    {
+      "@type": "PropertyValue",
+      "name": "frame_count_max",
+      "value": 690
+    },
+    {
+      "@type": "PropertyValue",
+      "name": "frame_count_mean",
+      "value": 197.11
+    },
+    {
+      "@type": "PropertyValue",
+      "name": "favos_20_videos",
+      "value": 100
+    },
+    {
+      "@type": "PropertyValue",
+      "name": "favos_40_videos",
+      "value": 100
+    },
+    {
+      "@type": "PropertyValue",
+      "name": "split_overlap_videos",
+      "value": 0
+    }
+  ],
+  "distribution": [
+    {
+      "@type": "cr:FileObject",
+      "@id": "JPEGImagesZip",
+      "name": "JPEGImages.zip",
+      "description": "ZIP archive containing video frames under JPEGImages/<video_id>/<frame>.jpg.",
+      "contentUrl": "https://huggingface.co/datasets/snu-aidas/FaVOS/resolve/main/JPEGImages.zip",
+      "encodingFormat": "application/zip",
+      "contentSize": "5018261297",
+      "sha256": "56077e69e1b0c27c3d5439732b69ce5e9fe8cd801c04fe40cc8cdc1ed7384171"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "AnnotationsZip",
+      "name": "Annotations.zip",
+      "description": "ZIP archive containing indexed PNG annotations under Annotations/<video_id>/<frame>.png.",
+      "contentUrl": "https://huggingface.co/datasets/snu-aidas/FaVOS/resolve/main/Annotations.zip",
+      "encodingFormat": "application/zip",
+      "contentSize": "81461764",
+      "sha256": "11afae990717fb6938017d77f28d0025108a0dbbc7feeda53cf6ad00c980beff"
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+    {
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+      "@id": "Favos20Split",
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+      "contentUrl": "https://huggingface.co/datasets/snu-aidas/FaVOS/resolve/main/favos-20.txt",
+      "encodingFormat": "text/plain",
+      "contentSize": "3300",
+      "sha256": "06a0f87cd07e3ae51eb67b000a911a82eeadf032afe7758f925c7cbf1e184787"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "Favos40Split",
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+      "description": "Evaluation split containing 100 video IDs.",
+      "contentUrl": "https://huggingface.co/datasets/snu-aidas/FaVOS/resolve/main/favos-40.txt",
+      "encodingFormat": "text/plain",
+      "contentSize": "3300",
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+      "name": "Annotation label masks",
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+      },
+      "encodingFormat": "image/png",
+      "includes": "Annotations/*/*.png"
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+  "recordSet": [
+    {
+      "@type": "cr:RecordSet",
+      "@id": "masks",
+      "name": "masks",
+      "description": "One record per annotated frame. Join frames and masks by video_id and frame_id. Masks contain integer label pixels, not one record per object.",
+      "key": [
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+        {
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+      "field": [
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+          "@type": "cr:Field",
+          "@id": "masks/path",
+          "name": "path",
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+          "source": {
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+        },
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+        },
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+          "split_membership/split": "favos-40"
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+        {
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+        {
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+        {
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+        {
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+        {
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+        {
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+        {
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+        {
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+        {
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+        {
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+          "split_membership/split": "favos-40"
+        },
+        {
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+        {
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+        {
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+        {
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+          "split_membership/split": "favos-40"
+        },
+        {
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+          "split_membership/split": "favos-40"
+        },
+        {
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+          "split_membership/split": "favos-40"
+        },
+        {
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+          "split_membership/split": "favos-40"
+        },
+        {
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+          "split_membership/split": "favos-40"
+        },
+        {
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+          "split_membership/split": "favos-40"
+        },
+        {
+          "split_membership/video_id": "8d3c0469eee6e9d09eeb59fae481af0a",
+          "split_membership/split": "favos-40"
+        },
+        {
+          "split_membership/video_id": "34ef04cd9fe808c3b69855fd559c6f0a",
+          "split_membership/split": "favos-40"
+        },
+        {
+          "split_membership/video_id": "f91be6e652955638cfcd765284efbd64",
+          "split_membership/split": "favos-40"
+        },
+        {
+          "split_membership/video_id": "42fb18ae777530addb2d71c8bd97e9b8",
+          "split_membership/split": "favos-40"
+        },
+        {
+          "split_membership/video_id": "6a6ce5aaf815cd2e8788d220d5b758a6",
+          "split_membership/split": "favos-40"
+        }
+      ]
+    }
+  ]
+}

source_provenance.csv

@@ -0,0 +1,201 @@
+video_id,split,source,source_media_id,media_license,attribution_status
+510ca352de434ce047880f09b49d4fb1,favos-20,YFCC100M,0ab9e3682ed76a764a62249b07349,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+79e6485ce65bcff58059665348851c3a,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+423e5ffc5bced29d9ad33aae06f672fd,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+d7cc905aff0a9c4337ae23def1152f62,favos-20,YFCC100M,1876c930771a532d507b62b4426bf952,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+1763fc52bde3718770285f2f105a11cb,favos-20,YFCC100M,0b5f265c28239e24f3596aba45939d3,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+d4edc6d59d1273f8c57041a073f8025a,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+ff1222464c9dca5e29dd249e70217051,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+e628894ab73cdb0976cfb28900459f85,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+8274ee49efaaeeb44fecee4c4c07e4df,favos-20,YFCC100M,16b56646b1289bcb3172a1ba6eab8af,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+2f4cb6ffb406a4dc10074e1138fef7b9,favos-20,YFCC100M,053297c12f337fe11416f8b9b79fabd,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+c23cc5bf4c7c04233ad9a3e8f137c21b,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+bee9a94d93e00c24576985f359af91e7,favos-20,YFCC100M,18b398bea4fb964fde3a276922b79094,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+00c92e9a7ec54d0c3e857c157103f99c,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+153b704766c803680be1069f23866c0d,favos-20,YFCC100M,1378237786cf5fb37b6eb5d25a1e6,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+1e5d0cc1ba9e55408e46837424b288a2,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+0a6f61f31a7c26f6218bc88c089efad6,favos-20,YFCC100M,177ca563ab4291b32280c2d64a2f3313,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+5f5167989358d014efc38ccc795b5b06,favos-20,YFCC100M,1581dc9543bf1a9d8133191d23e599,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+7e833a447115188d4eb75a47cb199a93,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+0ee9797f6ee00377c04fc8641e6c34b9,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+85fe83123ac1f1fda088cc84d06407e7,favos-20,YFCC100M,121c15cfe38873fbfb7b707cb358,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+38da9241ba734fc0c459618c7486eb89,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+25957feda7d3739aaf14c005feee1ef4,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+c87e2a1aecabf67710f8da466f590119,favos-20,YFCC100M,191bf9fc7d676806ca513399c1782cc,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+0dde0554b6c9fed87fab441945b174cc,favos-20,YFCC100M,074309fff29e2b5558eb32aba33e27,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+f3227d95d567045a0756d262af5f8810,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+9ebd5ab53f3fdc74e9b5779d7d33a0bc,favos-20,YFCC100M,1144b84adad17a63977bedb0a656cac7,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+acdf7be22f237731a575509e0f8bd562,favos-20,YFCC100M,10591ee3f59ca4b890c1a7b4416f77,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+d3eae82414483d0ed4b307c2ed9308dc,favos-20,YFCC100M,1a3d2e410f2b2d2d87720d74d3b1a,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+34267d0c93e49c569ba8385af38d6c3c,favos-20,YFCC100M,0d59bc7e85c6b361d4d61c8ecd8ac,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+6d1b4a7a8b9e62ecbd0f059aba830fed,favos-20,YFCC100M,0dc5911b4ed16f93d13ea529d783c1c,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+8cc0996707f3c98847d6accd398cae4a,favos-20,YFCC100M,16787f2203534f01148e69f8bfc76d,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+c7efe295f111c89c5446c1896635c56f,favos-20,YFCC100M,11c2bea4bdabf716608c3ae0cb1427,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+dd3faeadfc531bb409591733db39e91e,favos-20,YFCC100M,18fce6322e209de0719a9a8ea58ac3d,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+7d7932c43d06cf7009bc77b5fb5887a7,favos-20,YFCC100M,109cac4ed080298ad725b3c4652355da,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+a2269e73813affec4f49c6febd85f93d,favos-20,YFCC100M,177a40b3f0bb9026249a13f6f035c3a9,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+b82baa030353a7072908f27342f9de0e,favos-20,YFCC100M,16b7e99e9c98e1449a9b85a8ad939b94,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+fceb1e96b99293ca080b76fd678b4b6b,favos-20,YFCC100M,1050686982fea66c27a957c1af434ea3,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+85883f9eb511a404cbb1db27297b21e7,favos-20,YFCC100M,1628a4e03b6fed259e429aec852b9bee,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+979098af4c56441a25dadecbee5e69e2,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+c80d646e03734936754a6ddbb458afc3,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+da0940b2ccd52aad70867952bb3cf6e6,favos-20,YFCC100M,18589d92c1eb34dfe776ce85eafbd8aa,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+7bacee56c447ffab952faa788cbd5c17,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+9fc9ab7f048a1340fdd97ae78b8f2806,favos-20,YFCC100M,0b7416092ad7b3d56bc1b62ace77634,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+19c78585aa31b4d07a914de97a7e4b66,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+64e63ff853a8a4543e72538c43a952ac,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+51ba04e5ce9ac6b0dbd733701b390e2b,favos-20,YFCC100M,1221bcb3c74aeeefc1be85fc909f169c,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+96aa657b5e118fa1968f4cc5193a336f,favos-20,YFCC100M,132de7a6eca13f907b162a7f62596,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+bfbf0477617337d3eaff9b7fcf3ebd68,favos-20,YFCC100M,11237d63a728a55a8069d74a48b3cce,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+e61f89e98345af7a873f262ec554ca56,favos-20,YFCC100M,011a75954e46977850925cc4eb6b68,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+9f29fb0d57673bf3980d991555ea5220,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+50b6658d8d2710fa42ccda4386198584,favos-20,YFCC100M,15b54133abc6846dc4fd6ccbde9ee569,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+90505bb788b5fedc7d0a01e7fd0df4d0,favos-20,YFCC100M,13c86d2b512fbf4f7fa6c459ba31b55,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+d8e3a1ee59b4a01d9935fcf74897a993,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+de24a6d99245d646a211d8238766f4ef,favos-20,YFCC100M,12d78b90557f2fbb391419653eb54f3,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+7a7e24b51fc6d4b6d81e6f95eb279c37,favos-20,YFCC100M,13b3ec373cb38965a50d16231a4928a,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+5e1e500cac40625eb6838427411a5708,favos-20,YFCC100M,0498bc815b331645f1b9e0b47fc53,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+990b0902db2522a6b70391283b69d1c5,favos-20,YFCC100M,14a6234734e6d858e72b7b40dfcc77,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+1b3910140cae94b1c8ff9b50496faee2,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+2ef88ebd235b393d723838f59856821e,favos-20,YFCC100M,1918578236a83359ea8264433aea,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+995c7b782b8cdf7eb7384e4817185d2e,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+3b376c82b85ff4285a4722ca312f84d8,favos-20,YFCC100M,19746e334adc775ca86eb1750a9fce,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+270d5b7afd61336af86b020d20deb765,favos-20,YFCC100M,13ca9ee9c2a2a52f497f2b5f22a491f6,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+ee210b1ce55ef31ef383aebda8a4341b,favos-20,YFCC100M,13c58fabb5348f4df0a64bc7c09ce247,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+2ee8130f4ea648a3484b9e9e2b55637c,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+61c8d0df22325001b0afba3fabcdf882,favos-20,YFCC100M,155e8bcaa81343d6cdd43f5875b55a4,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+e5603ce1b13cc4ebc56afe013ee3c0c8,favos-20,YFCC100M,16947d17f984a7d981c3e6b73d2e82d3,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+7e2020fb5885e05fd13d4ad2e932550b,favos-20,YFCC100M,11f6dc225fa8405141ff25c238a4baf0,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+d226434439d033ee9fbd501b6cc4d5f9,favos-20,YFCC100M,1a37f448d0ee5b8d6e1beca84157d3,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+83c3e21fba30c40d5f28f33b056ba374,favos-20,YFCC100M,10bcc1de5487f44ad83af47928207e41,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+3cd95d40559fa81acba263bd77e59da6,favos-20,YFCC100M,0587fe1ad8d1205907af0a25c15af,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+f3598c3a5b2d094cb3fcf2dbced80e52,favos-20,YFCC100M,16e535b4f8b6736693de2c4a481a9df,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+3c36b6c7d6d6120f496666706be114b1,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+8c8f9d28ca4f35048a8b1d610150efc5,favos-20,YFCC100M,141f224a3f6546a6eb56337695def7e,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+72cb7a00ca57a18c4e3fb852b78c33ef,favos-20,YFCC100M,151ceeca6595a56b1a1113ac69a8bc2,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+d7cb2e252b48cb82c329c64b043b0421,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+dfbac4e6a082e805468529a391e2b594,favos-20,YFCC100M,1379fed762bd271e2998b4705281b498,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+4538bc2348c23748c7146071ae7b48b3,favos-20,YFCC100M,17a33feb33b6aa16664f88b32392a130,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+58fb9ec9133eb0f56ccb1d0f4fe754d4,favos-20,YFCC100M,061679cbd72fbb17da46e99121814a9,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+05385ba87b8eb13f760700e31dd6f95a,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+5025e98042f5fc3e54bbc9f81151bd7e,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+c4f2af9ae8283cfd84c8f6a5f29f3260,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+5a33a5383d9754278cdca828f4186567,favos-20,YFCC100M,10bb933e958080de8a3d3c6dca4c23da,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+b3865a1c6b1033408c39e940d6dd1059,favos-20,YFCC100M,188cbf635e5edb283a7e15c5b9ebc,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+145228a3367ae38b3873004db7271788,favos-20,YFCC100M,17a22fbeaebda64321f57de72e1dd,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+3327744fbe807ee40e7e2b64609817db,favos-20,YFCC100M,10213c6bed83fb33e38881f75be647f3,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+b791939c01330564e1c8673171219161,favos-20,YFCC100M,12b3457c9010fa31921fc988df59ac17,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+8317e25281cb9402701973753dc999b0,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+f84c7f2017aaec513f6c886fa9a5654a,favos-20,YFCC100M,1413e13ceb6fd5d46f3fb7d834ba7499,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+7f661ad675d0139b2645293e6d7b91e8,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+b4f0e4d5c1041249d8f6e9bf41763695,favos-20,YFCC100M,132155ef8aadff9212ddb558bb2516c,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+e0b0165909cd2a6ffe20d3f809f4a937,favos-20,YFCC100M,1094fe8c35f2a8f0c86ea989745330d,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+99b0480e105bc4a1410c39daa7696b17,favos-20,YFCC100M,16e5f4501ca341acb6907d84ee6fa749,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+43f0500520c50fc31c56e28167f6e51b,favos-20,YFCC100M,17144caea34f946869acbe2169138dc,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+496957948545345c33b8837dc236f96a,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+6684eb2794511605a0604c1c472f6e5f,favos-20,YFCC100M,0a959c14ae0d9defef64e38faec8f,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+1997593e511d401515fef7479057e6bb,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+fba1e215b4e94802573bf986c2445c54,favos-20,YFCC100M,027121963df827c83ad19c8a18340d5,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+f876c2f2a3ca802ae1109f81a70bb3c0,favos-20,self-collected,,CC BY-NC 4.0,FaVOS authors
+ed1a4227cb95f651078e3e6f78eb4ce0,favos-20,YFCC100M,1855b6fbb165b29d57b9a15d9baf43a0,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+92d12c7fa5635a251de006b7b7c4eba6,favos-20,YFCC100M,188ec2196d2ec0e938a2e0c6521e63d8,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+4750de5a4ed73ac3ed7eda996d0267d7,favos-40,YFCC100M,15d3bceff29ac82dacf3d4c2bff66,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+94253e245eac9a7966f320ddc12aef77,favos-40,YFCC100M,168dba4acd397f22b958ba403496c37a,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+d4daf55888ec2412f3364d727ea59676,favos-40,YFCC100M,117cf2b2df126f27d87e1a3070aa50b4,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+56a8974858d46772b14884c3b3818acc,favos-40,YFCC100M,1490b9fa2b57b6b1c5c9878a52b42bd,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+8171d12d7221df620aca9604337011ba,favos-40,YFCC100M,17f28d70d1c8dd7d9c404098bc9455,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+aabcaea6a028bbb9d493d5d9e54a3aa2,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+cc417bba46653c48e721b868aa22f8d0,favos-40,YFCC100M,139e8e3aab80c50a61f261e5729acf7,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+825f26bdc37c37f5a3b126d9ddf21294,favos-40,YFCC100M,19d6f2a08e18a1b32ae611f358d3b5d7,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+7579cb830d7d9f60a4df6d66919141bb,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+ea004c817ad6ed08772b078395f40ea4,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+188153a03c31d5a3e177a792a39609aa,favos-40,YFCC100M,19299865d67d16135fe63ea36bd2ef1,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+3fcdb07cf93310be97fb559ac63ec6ee,favos-40,YFCC100M,13b261a557c7f5d4bbedd97f3425453c,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+3e5e416c827648535a0b7ce27e99b8f7,favos-40,YFCC100M,172db147388dd73335384aedc3dfdb13,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+890634d1700d7c1c1ca7f3854b25cc15,favos-40,YFCC100M,18bc24daa5d771fa697ead31e7934b,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+fd3b065ab8013a2e79ed62be1c7b8432,favos-40,YFCC100M,16d14167e2b23871baeb44a8a4f46b76,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+bad2a11729d1433453255ed44a252894,favos-40,YFCC100M,18c6c0bc4592c9da6bfb64f62def7f32,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+7f70a2127da7fa077f4c2f25b8856115,favos-40,YFCC100M,135b1cf18f3eaf8b8652c10b32fce35,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+0961c51cfd94d7cc6027adb8c5ea351a,favos-40,YFCC100M,107cf035789eb6d1d42c6ca8f1c8d4ef,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+cce57a8b3f84e83c9e2b4cdd5e912df1,favos-40,YFCC100M,18574a99b6a58a4fdb19245da59c5670,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+7023cddaddd36e9d1aa893b6b2ffefb7,favos-40,YFCC100M,18607480a2371e4cce99b2b33a1eeee3,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+d098c0baf60420840561bbb1d8c11f03,favos-40,YFCC100M,063fde01b98651c773931cb529f635,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+80727c8eab53b9d4d3f2c65dd6260f4f,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+14683ed05ff1f4249a866300fa740afd,favos-40,YFCC100M,1351a5b546a2d67ea23fad27c30e896,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+11507069f926df5d0e120a0e925a44f4,favos-40,YFCC100M,13831932c834b93c39e3f99e97a25e5,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+e25386a824771c3830277870e219330d,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+9aeb0ae9f74e2cc72dc9ab05ed827509,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+9a3fa34af8963d03315cda02686f8a6d,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+be05d0f2a0a11b41cdf27dd786a7d374,favos-40,YFCC100M,1a13489524accb7012b1c98b893549,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+d81bcac5eb3b1ba82920c01f2bcff550,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+bc767f91bed2677aa84edc1cf6cc4d8e,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+eb97baf602d734a4f79fc91b84d5ab90,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+6038639557c363c42eb271cfc2bc14c9,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+0ce210231a7803ee7ea39873190b446c,favos-40,YFCC100M,17523b24c941bf182da865bf113a744,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+c17639673399150246480ad5944724c2,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+507e1dc1fea9826562b7ec570e242fa0,favos-40,YFCC100M,101b9e61f1b786f20c2bb423f5e91e,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+ed7a8041a84fb90ba764af9639f71120,favos-40,YFCC100M,15e81e8ca62990834940cf685ff5cb4,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+639d041857f19c990a6a9bfb2f681f1f,favos-40,YFCC100M,0a3522f7ec8c57e41e4b68fc0af927f,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+b3c8a9f1e3981587a0cc318c020389fc,favos-40,YFCC100M,123eba8fc9739611fe4c2c71782a046,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+956dd29b84e65251d74dc0921ff00d3a,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+3c541ecada626e6a7490f0d466e5cb5a,favos-40,YFCC100M,119140cc046da7d6b3cea1f9b6f3077,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+027361154062d57242859b91bb31f458,favos-40,YFCC100M,0ab4638080696591fb27818e2256,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+ce642bffcf1b4f332d3ee3194aa8c910,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+d9ca643c71220034c1f509bf3bb7bb6c,favos-40,YFCC100M,0a0385aa2b7d63a53bad43367ab8ff,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+6548bf59ebdbb9d0f87a86e5c0f62008,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+46021c4ab2273a426179f20746a64056,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+622a28c3b083546daf33020da1a60d8b,favos-40,YFCC100M,103596c52e4d16b0f21c9c1db6cd72d,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+4fd9b7e01f69ae0bc7010c704413ee7c,favos-40,YFCC100M,139668820dbe79039393ba96fbd4872,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+9493e12c06bd851f232449da1ebeb455,favos-40,YFCC100M,11ae6d67448fbcd5555f55852d98677,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+e3097db434b19ef61e18be0aad0998a4,favos-40,YFCC100M,17b18e896e0c07bf434c4d6db0ad,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+a9fbc0b25ef74ddf903793f1ec5e3d40,favos-40,YFCC100M,19c23ae105473b15fea123ff7c8d0da,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+e85ba3fcc2ca9aef56eb4e24f51b557a,favos-40,YFCC100M,13236d9f2cb769864b8f1683b75ab37a,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+083c4d4e5e9a5a797fb73861f6e0db7c,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+6d5e9284da79564aa97332349105ae69,favos-40,YFCC100M,138615d35a34ff1ead70639ebc59e36,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+6f020ff2874d30ca512629d4173ce9b1,favos-40,YFCC100M,133f451f7a5f95918a37c8341b3839d0,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+261bc95d11516aca19aa790652054a49,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+6482e2044989f4c0188cc6c7fa04ed39,favos-40,YFCC100M,17adb0b9fab28cfb2a15dd38457aeb6,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+1b3aa93dcd35bcc2969b6c6ea3df8957,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+6c84d376b4525a0987f612911d588a17,favos-40,YFCC100M,13bad36941dfe778aab42e22725ccc73,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+b9f4a9bb89e5d0e772fe89e026489c84,favos-40,YFCC100M,04deedbef1b30d376ddc3ce646b4d9,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+0fe93221b3cfc9d3144d986ed4d154dd,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+8a404976cbb72a1b4420cbaeebf779df,favos-40,YFCC100M,197b2f5383ed56568b764a713768a758,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+31794cb13399f114ca2d48ab9705e263,favos-40,YFCC100M,180b736ac79e9f3357d32db9d3f387,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+1b1e5e98ceadae3c97ec3e697edb504e,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+74f3fdfbdb7e1d9c77dbb8393a2930c4,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+193986c0dadff682425d2503994f6f74,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+6fa3bc477c4d141e2bc02536fd9d341d,favos-40,YFCC100M,053f5b39d8dd49484bda9437bcc464,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+443d366bdbafde1df65854c63999f276,favos-40,YFCC100M,1252359a4d55d55c8a299daee49f,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+a5cbeceefb0bbe01164f9d071265515d,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+613959df1f96df73142c053ef4149521,favos-40,YFCC100M,04f3bfdac533ae26be8a81c98049f4,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+341abea5d530fb03c0543c77e9b7547a,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+0e3606e492c97f16b9b00938992b43fa,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+25095ccdf53e5212769155a3ac35883a,favos-40,YFCC100M,19b3bbd224485d68556e53da5fc43cb,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+e632f5529cdaa16297f6ece0d85f528a,favos-40,YFCC100M,13719f4ee3e7618bcf7274d7c8a9c6c,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+3d0fd71dbd7995dfe9790b3b6664ec4d,favos-40,YFCC100M,11542369a1e6961dd7d7d5f1ed8619a9,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+905cd1071101c1f5021580349d81b8d7,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+d1ece9bbd0b7943b807d7a6bca660521,favos-40,YFCC100M,1251829876232a904ba9f415cb6a99f2,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+5c392f7e62c0833639b9f294f4f4047a,favos-40,YFCC100M,112357a4c3983382c29dd3b270d77a42,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+ab9850dc9ce66da7a38e2f31de75c3be,favos-40,YFCC100M,10c53da0382a49597bae433bf61a52,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+598aa6e379588116c20fbe0c9ac618cf,favos-40,YFCC100M,0259636efa3727156a91742783dc25a,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+4fcac6d55bba3bdc0cf7b0173f9fc3bf,favos-40,YFCC100M,19c8714c3071d086cc6e9b51aa6bd352,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+bf9167f01ab7ab3a2fa9479cf6468575,favos-40,YFCC100M,13456dfa9821f13930c164f88a78fc2,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+67d270ad20e288b49dbe8d4118da4dca,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+7f63e595c5852986a6e5577c1d10f081,favos-40,YFCC100M,101a9458ee4b59b02a9dfa3aaae18d9,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+b9458c4ddd1d97ecb10488394fbaae3b,favos-40,YFCC100M,19fa2f22a849b26ba86a832a2277457,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+e446850c7bb6f71273bb2980a57e61e3,favos-40,YFCC100M,145c9515239957a083dea9ec83f98d92,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+9599d68f7d2d5a42a048c7fea7160de6,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+0ddb3ccdb8cd010c226b30a13da8c867,favos-40,YFCC100M,177b2877975b20c7721c98a693e13abe,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+8e0d47249ed76464abd46a9099d36988,favos-40,YFCC100M,13a76853a69d5de87dce858784d67,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+5c57659d33c5c763be2d39c789c24fcb,favos-40,YFCC100M,0f372d1f5c6baf64769d0682f3d716e,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+73e765d9e7d10d5e352e0a0ca8872939,favos-40,YFCC100M,135c2da331e918c8f6ab1fb9d9e9fda7,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+c3382e7f8c961173514ba7c0e6ea29ff,favos-40,YFCC100M,101a2bbb85a8161bbaa63b23a9757e6c,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+18c22726d269d275640765ce76b6214e,favos-40,YFCC100M,1618a7d2f063bfa6a841788d6f4847c7,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+0318cc320c7f8cde3d189e12e4ad49d1,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+e55bd1ae4cfa387a56402d567bfba8ac,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+e374cccf987d407ce4d4b76f2fa08118,favos-40,YFCC100M,1154c032de267f2e25454c01cb976a4,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+8d3c0469eee6e9d09eeb59fae481af0a,favos-40,YFCC100M,15513e2e3976d89ad13dd0d156d3,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+34ef04cd9fe808c3b69855fd559c6f0a,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+f91be6e652955638cfcd765284efbd64,favos-40,YFCC100M,10e56984dabe9c9bec3c14ad4b8b4a67,Original source license; see LICENSE.md,"Per-video creator, URL and license not present in available inputs"
+42fb18ae777530addb2d71c8bd97e9b8,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors
+6a6ce5aaf815cd2e8788d220d5b758a6,favos-40,self-collected,,CC BY-NC 4.0,FaVOS authors