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file mode 100644 index 0000000000000000000000000000000000000000..e1df2258457227cec6864e13143ee7d0bbccbbc7 --- /dev/null +++ b/README.md @@ -0,0 +1,204 @@ +--- +license: apache-2.0 +pretty_name: OneStreamer-1M +language: + - en + - zh +task_categories: + - visual-question-answering + - text-generation +tags: + - streaming-video + - proactive-response + - video-question-answering + - caption-memory + - temporal-grounding + +--- + +# OneStreamer-1M + +[![OneStreamer-1M task taxonomy and streaming data synthesis pipeline](assets/data_pipeline.png)](assets/data_pipeline.png) + +*Adapted from the paper: task taxonomy on the left; streaming caption and QA construction pipelines on the right.* + +**Task coverage** + +| Task family | Main supervision | +| --- | --- | +| Proactive Caption Memory | Hierarchical and flat captions for local evidence recording and event summaries. | +| Proactive Interaction | Continuous descriptions, alerts, reminders, counting, visual interaction, contextual feedback, and procedural assistance. | +| Proactive QA | Questions answered as a stream unfolds: general, dialogue, temporal, gesture, anomaly, and procedural QA. | +| Perception & Memory QA | Current and historical evidence: general/spatial QA, grounding, counting, prediction, procedural reasoning, answerability, identification, and risk reasoning. | + +## 1. Dataset design and construction + +A training dataset for **perception, memory, and proactive response in streaming video interaction**, introduced in [*OneStreamer: Unifying Perception, Memory, and Proactive Response in Streaming Video Interaction*](https://arxiv.org/abs/2610.01762). + +The curated collections include **Streamo, JoyAI-VL-Interaction (JoyVL), MMDuet2, ViSpeak, StreamForest, VideoChat-OL, Seeker, and VST**, alongside OneStreamer-Core. The appendix groups upstream sources by collection and task; a source list in the table describes that group rather than assigning every record to all listed sources. + +
+Full collection, task, and source breakdown, adapted from the paper appendix + +**Proactive Caption Memory** + +| Collection | Task | Upstream datasets / sources | +| --- | --- | --- | +| OneStreamer-Core | Hierarchical captioning | YouTube-Collected | +| OneStreamer-Core | Flat captioning | YouTube-Collected | + +**Proactive Interaction** + +| Collection | Task | Upstream datasets / sources | +| --- | --- | --- | +| OneStreamer-Core | Continuous description | COIN | +| OneStreamer-Core | Active counting | PerceptionTest, THUMOS | +| OneStreamer-Core | Alerts and reminders | TimeLens-100K, TimeLens2-93K | +| Streamo | Alerts and reminders | ActivityNet, LLaVA-Video, QVHighlights, DiDeMo, QuerYD, TACoS | +| Streamo | Continuous description | COIN, YouCook2, HowToStep, ActivityNet, QVHighlights, LLaVA-Video | +| ViSpeak | Visual interaction | ViSpeak-Instruct | +| ViSpeak | Contextual feedback | OOPS, FunQA | +| JoyVL | Alerts and reminders | YouTube-Collected, MM-understanding-processed, Remind-once, TimeLens-100K, Molmo2-VideoCapQA | +| JoyVL | Continuous description | Shot2Story, HoloAssist | +| JoyVL | Active counting | Molmo2-VideoCapQA, VideoGPT+ training data, Molmo2-AskModelAnything | +| JoyVL | Procedural assistance | HoloAssist | +| MMDuet2 | Continuous description | Live-WhisperX-526K | + +**Proactive QA** + +| Collection | Task | Upstream datasets / sources | +| --- | --- | --- | +| OneStreamer-Core | General video QA | MAGQA | +| OneStreamer-Core | Video-dialogue QA | TVQA | +| OneStreamer-Core | Anomaly QA | UCF-Crime | +| JoyVL | Temporal QA | VideoGPT+ training data | +| JoyVL | Gesture and expression QA | Biaoqing-zh, Shoushi-zh | +| Streamo | General video QA | Ego-TimeQA, LLaVA-Video | +| Seeker | General video QA | LLaVA-Video, LongVideoDB, YouTube-Collected | +| MMDuet2 | General video QA | Live-WhisperX-526K | +| MMDuet2 | Procedural QA | EgoExoLearn | + +**Perception & Memory QA** + +| Collection | Task | Upstream datasets / sources | +| --- | --- | --- | +| OneStreamer-Core | General video QA | EgoQA, Ego4D, COIN, Shot2Story, YouTube-Collected | +| OneStreamer-Core | Spatial QA | AVA, YouTube-Collected | +| OneStreamer-Core | Future prediction | Ego4D (GoalStep) | +| OneStreamer-Core | Procedural QA | COIN, YouTube-Collected | +| OneStreamer-Core | Counting QA | PerceptionTest, THUMOS, YouTube-Collected | +| OneStreamer-Core | Person identification | YouTube-Collected | +| OneStreamer-Core | Answerability judgment | EgoQA, YouTube-Collected | +| ViSpeak | General video QA | ViSpeak-Instruct | +| ViSpeak | Gesture and expression QA | Social-IQ | +| StreamForest | Spatial QA | LaSOT, AS-V2, RefCOCO, Visual Genome, AVA, GOT-10k, OnlineIT-Drive | +| StreamForest | Temporal grounding | ActivityNet, COIN, LaSOT, Charades, HiREST, InternVid, QuerYD | +| StreamForest | Future prediction | OnlineIT-Drive | +| StreamForest | Risk reasoning | OnlineIT-Drive | +| VideoChat-OL | Spatial QA | AVA | +| VST | General video QA | VST-Training-Data | +| VST | Counting QA | VST-Training-Data | +| VST | Answerability judgment | VST-Training-Data | + + +
+ +OneStreamer-Core also includes alert/reminder annotations from **TimeLens-100K** and **TimeLens2-93K**. + +OneStreamer-1M combines newly constructed **OneStreamer-Core** data with curated streaming-video training collections. Its supervision connects **what has been observed**, **what should be retained**, and **when a response should be produced**. + +## 2. Metadata release and usage + +Annotations are organized by task family, collection, and task in JSONL files. Each line is one training record and may contain multiple inputs and outputs. Records may share a video, and some tasks use images. + +The release provides readable annotations and relative media references. **Video, frame, and image files are not included.** Media paths identify the expected dataset layout; processed or cropped assets may require a matching media package or a mapping from their original source videos. + +### Files and fields + +```text +README.md +assets/ + data_pipeline.png +Proactive_Caption_Memory///*.jsonl +Proactive_Interaction///*.jsonl +Proactive_QA///*.jsonl +Perception_and_Memory_QA///*.jsonl +``` + +| Field | Meaning | +| --- | --- | +| `schema` | Metadata format version: `onestreamer-public-meta-v1`. | +| `id` | Source record identifier; not guaranteed to be globally unique. Use the annotation file and line number to identify a specific record. | +| `source` | Dataset or annotation collection. Mixed-source collections may retain their collection name. | +| `classification` | Task `category`, data `collection`, and specific `task`. | +| `video_name`, `video_path` | File or frame-directory name and its dataset-relative path. These fields are also used for image records. | +| `media_type` | `video` for a video file, `image` for an image file, or `sequence` for a frame directory. | +| `sequence` | Frame storage and FPS; optionally includes a known filename pattern and index origin. | +| `video_ranges` | Optional observed input ranges in seconds. These are the ranges used by this record, not the full media duration or response durations. | +| `image_size` | Optional annotated `[width, height]`; does not specify the normalization scale of bounding-box answers. | +| `prompts` | Ordered text inputs with a local `id`, `kind`, `at`, and `text`. Explicit `Speech:` inputs are marked as `speech` context. | +| `timeline` | Ordered state intervals and textual outputs. Content outputs may use `prompt_id` to identify the active question or instruction. | +| `videos` | Present for genuinely distinct multiple media inputs, replacing the top-level single-media fields. Inputs and outputs use `media_id` or `media_ids` to refer to them. | +| `system` | Optional original system instructions. | + +**Time representation.** `silence` and `standby` use `interval: [start, end]`; adjacent intervals of the same state may be merged. `response`, `observe`, `summary`, and ordinary QA `answer` outputs use `at` and `text`. A response is a single output event. The intervals retain the original state labels; they do not imply repeated response text. Source-specific loss masks and training-only sampling settings are not included. + +Times are in seconds and retain the source annotation convention. In this metadata format, `at` is the endpoint of the associated input observation window; it is not necessarily the precise time of an event described in the answer. `null` means that an explicit time was unavailable. Answer text, including any timestamps within it, is preserved. + +**Media references.** Video and image paths include their filename extension. Frame paths end at the logical video directory, with a trailing `/`; `video_name` is the directory name. Sequences originally stored as one-second MP4 segments use the intended **4 FPS frame representation** in this release, with filenames such as `00000_00.jpg`, `00000_25.jpg`, `00000_50.jpg`, and `00000_75.jpg`. These frame assets must be prepared separately. Existing frame sequences retain their annotated FPS, including sources at other frame rates. + +A proactive QA example, showing selected fields from one record: + +```json +{ + "video_name": "ytb_ls8tmkfD7S0", + "video_path": "LLaVA_Video/1_2_m_youtube_v0_1/liwei_youtube_videos/videos/youtube_video_2024/ytb_ls8tmkfD7S0/", + "media_type": "sequence", + "sequence": {"storage": "frames", "fps": 4, "filename_pattern": "{seconds:05d}_{centiseconds:02d}.jpg"}, + "video_ranges": [[0.0, 6.0]], + "prompts": [ + {"id": "p1", "kind": "text", "at": 5.0, "text": "What event is the person with long blonde hair being interviewed at in front of a poster for 'The Beguiled'?"} + ], + "timeline": [ + {"type": "silence", "interval": [0.0, 4.0]}, + {"type": "standby", "interval": [4.0, 5.0]}, + {"type": "response", "at": 6.0, "text": " The person is being interviewed at a red carpet event in front of a poster for 'The Beguiled.'", "prompt_id": "p1"} + ] +} +``` + +To inspect the metadata after downloading the dataset repository: + +```python +import json +from pathlib import Path + +dataset_root = Path(".") # downloaded dataset repository +annotation = next((dataset_root / "Proactive_QA").rglob("*.jsonl")) +with annotation.open(encoding="utf-8") as f: + record = json.loads(next(f)) + +print(record["prompts"]) +print(record["timeline"]) + +# Resolve a reference against your own media root. +media_root = Path("/path/to/downloaded/media") +asset = record["videos"][0] if "videos" in record else record +media_path = media_root / asset["video_path"] +``` + +Different source datasets can be stored under separate roots by mapping their path prefixes. + +## Citation + +```bibtex +@misc{zeng2026onestreamerunifyingperceptionmemory, + title={OneStreamer: Unifying Perception, Memory, and Proactive Response in Streaming Video Interaction}, + author={Xiangyu Zeng and Yuandong Yang and Zhiqiu Zhang and Yuhan Zhu and Xinhao Li and Qingyi Si and Dingyu Yao and Changlian Ma and Haoran Chen and Xinyu Chen and Yansong Shi and Junhao Zhou and Yifei Li and Jun Zhang and Chuanyu Qin and Chenxu Yang and Xinlei Yu and Kun Ouyang and Yuchen Shao and Qianshan Wei and Changhai Zhou and Jun Gao and Jiaqi Wang and Limin Wang}, + year={2026}, + eprint={2610.01762}, + archivePrefix={arXiv}, + primaryClass={cs.CV}, + url={https://arxiv.org/abs/2610.01762} +} +``` diff --git a/assets/data_pipeline.png b/assets/data_pipeline.png new file mode 100644 index 0000000000000000000000000000000000000000..e3b96cb556ec68cc65f4f7c1f0a455fa07de0016 --- /dev/null +++ b/assets/data_pipeline.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:78de554231657ba93db2f2b63b35462303797720fcd352d4ae24fa2b3cbb723b +size 454324