Datasets › V2VBench

V2VBench

Introduced by Wenhao Sun et al. in Diffusion Model-Based Video Editing: A Survey26 Jun 2024 archive 2025-07-28

V2VBench is a comprehensive benchmark designed to evaluate video editing methods. It consists of: - 50 standardized videos across 5 categories, and - 3 editing prompts per video, encompassing 4 editing tasks: Huggingface Datasets - 8 evaluation metrics to assess the quality of edited videos: Evaluation Metrics

For detailed information, please refer to the accompanying paper.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 2 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • V2VBench

1 variant name, as the archive lists them.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections