---
pretty_name: GeoFlip Preview
language:
- en
license: other
license_name: restricted-research-use
license_link: https://huggingface.co/datasets/DreamingLow/GeoFlip/blob/main/LICENSE.txt
tags:
- image
- video
- physics
- image-to-video
- benchmark
- arxiv:2610.42002
configs:
- config_name: inputs
  data_files:
  - split: evaluation
    path: first_frames/**
---

# GeoFlip Preview

**Benchmarking Geometry-Sensitive Physics in Video Generation**  
[Paper](https://arxiv.org/abs/2610.42002v2) · [Code](https://github.com/itsnotacie/GeoFlip) · [Project page](https://itsnotacie.github.io/GeoFlip/)

**482 paired tests · 964 core reference videos · 6 physical categories**

Authors: Yuqi Li*, Junming Liu*, Bowen Hu, Ruize Niu, Huiran Duan, Ming-Hsuan Yang, Yingli Tian, Hao Wu†.  
*Equal contribution. †Corresponding author.

GeoFlip includes first frames, video-generation prompts, simulation references, evaluation labels, baseline predictions, and scoring code. Alongside the 964 core conditions, **16 neutral controls** are provided separately, for **980 conditions** in total.

## Quick start

Follow the [scoring quickstart](docs/QUICKSTART.md). To use the toolkit included with this dataset:

```bash
python -m pip install -e './toolkit[download,video,http]'
```

Download scripts support model inputs only, evaluator metadata only, or the complete package, pinning one HF commit and verifying SHA-256 checksums. Give the model only `inputs/manifest.jsonl` fields and the selected first frames. Never provide evaluation truth or reference futures to a generator.

To score existing generated videos, create a submission JSON mapping each opaque condition id to a native video file. Validate, obtain event/structure judgments, and run the deterministic scorer.

```bash
geoflip validate --data . --subset paper-main --submission my-model/submission.json --out validation.json
geoflip score --data . --subset paper-main --predictions my-model/judgments.jsonl --out scores.json
geoflip baselines --data . --subset paper-main --judge gpt-6-astra --out reproduced-main.json
```

The last command reproduces the event and structure scores of all 16 paper models without API calls. All **32 main-table values** match after rounding.

## Files

| Path | Content |
| --- | --- |
| `inputs/manifest.jsonl` | Model-facing first-frame paths, generation prompts and requested timing |
| `first_frames/` | 980 input PNG files and image-folder metadata |
| `references/` | 980 reference MP4 files for evaluation |
| `evaluation/truth.jsonl` | Labels, task definitions, observation times, and prompt metadata |
| `evaluation/pairs.jsonl` | 482 pair memberships and same-first-frame flags |
| `splits/` | Frozen condition-id lists |
| `prompts/` | Judge template and task/label definitions |
| `baselines/` | Baseline judgments and the paper results table |
| `docs/` | Quickstart, metrics, frame sampling, and data format |
| `toolkit/` | Installable evaluation and download code with tests |
| `SHA256SUMS.json` | Integrity hashes for all included files except itself |

## Scopes

| Scope | Conditions | Meaning |
| --- | ---: | --- |
| `core` | 964 | Paired-reference inventory, 482 pairs |
| `auxiliary` | 16 | Neutral controls, separate from the core count |
| `paper-pool` | 720 | Historical selected inference pool, including four controls |
| `paper-main` | 442 | 438 core conditions and four controls, across 34 tasks |
| `cross-judge` | 346 | Earlier 342 core conditions and four controls |

Use the fixed ID lists in `splits/` for comparisons. Original partitions and pair information are recorded in the evaluator metadata.

## Metrics and prompts

Event correctness is class-balanced within each task and then task-macro averaged. Structural integrity is the task-macro fraction explicitly judged `clear`; uncertain, flagged and missing outputs remain in the denominator. See [EVALUATION.md](docs/EVALUATION.md).

Generation prompts are in `inputs/manifest.jsonl`; judge prompts and task definitions are in `prompts/`. See [DATA_FORMAT.md](docs/DATA_FORMAT.md) for original prompt text and video-continuation adaptations.

The paper's PSNR/SSIM columns use a separate 40-clip benchmark. Those aggregate numbers are preserved, but that benchmark's reference media are not redistributed here. GeoFlip reference-similarity diagnostics are labeled separately and must not replace the 40-clip values in the paper ranking.

## Usage terms

Dataset usage terms are in [LICENSE.txt](LICENSE.txt).

The paper's Opus evaluation was run separately; its raw judgments are not included here. Additional historical predictions are identified as Qwen3-VL-32B-Instruct according to their source metadata. These are separate results. The included GPT predictions reproduce all 32 main-table event/structure values.

## Citation

```bibtex
@misc{li2026geoflippreview,
  title={GeoFlip Preview: Benchmarking Geometry-Sensitive Physics in Video Generation},
  author={Yuqi Li and Junming Liu and Bowen Hu and Ruize Niu and Huiran Duan
          and Ming-Hsuan Yang and Yingli Tian and Hao Wu},
  year={2026},
  eprint={2610.42002},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}
```