datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
FiVE-Fine-Grained-Video-Editing-Benchmark
FiVE-Bench
FiVE-Bench: A Fine-Grained Video Editing Benchmark for Evaluating Diffusion and Rectified Flow Models
Minghan Li1*, Chenxi Xie2*, Yichen Wu13, Lei Zhang2, Mengyu Wang1†
1Harvard University 2The Hong Kong Polytechnic University 3City University of Hong Kong
*Equal contribution †Corresponding Author
💜 Leaderboard (coming soon) |
💻 GitHub |
🤗 Hugging Face
📝 Project Page |
📰 Paper |
🎥 Video Demo
FiVE is a benchmark comprising 100 videos for… See the full description on the dataset page: https://huggingface.co/datasets/LIMinghan/FiVE-Fine-Grained-Video-Editing-Benchmark.premiere-video-editing-trajectories
Creative Video-Editing Computer-Use Trajectories (Preview)
A preview release of computer-use agent trajectories from professional video-editing work in Adobe Premiere Pro (building vertical short-form social reels). Each step pairs a screenshot with a structured action and a first-person thought grounded in the editor's spoken narration as they worked, so the step-level reasoning reflects real human intent rather than a rationale written after the fact.
A sample of the human… See the full description on the dataset page: https://huggingface.co/datasets/contralabs/premiere-video-editing-trajectories.descript-video-editing-trajectories
Descript Video-Editing Computer-Use Trajectories (Preview)
This is a preview release of computer-use trajectories from experienced video editors working through client-style editing briefs in Descript: cutting vertical short-form social reels from source footage. Each session is a long edit, about two hours and a few hundred steps, and the editor's spoken narration was recorded while they worked and used to ground the step-level reasoning. Most open GUI-agent datasets cover… See the full description on the dataset page: https://huggingface.co/datasets/contralabs/descript-video-editing-trajectories.video-editing-evaluation-65f
Video editing evaluation: aligned 65-frame package
This package contains only the aligned 65-frame evaluation inputs and scripts for 419 FiVE-Bench cases and 20 VIE-Bench reference-editing cases. It contains no generated method outputs, prior metric CSVs, FiVE-Acc, NIQE, or other FiVE-only metrics.
Contents
data/inputs_65f.zip: source MP4s, 65 aligned source frames and masks, VIE reference images, and portable JSONL manifests. The masks and references are real… See the full description on the dataset page: https://huggingface.co/datasets/yanlinli/video-editing-evaluation-65f.FiVE-Fine-Grained-Video-Editing-Benchmark
FiVE-Bench
FiVE-Bench: A Fine-Grained Video Editing Benchmark for Evaluating Diffusion and Rectified Flow Models
Minghan Li1*, Chenxi Xie2*, Yichen Wu13, Lei Zhang2, Mengyu Wang1†
1Harvard University 2The Hong Kong Polytechnic University 3City University of Hong Kong
*Equal contribution †Corresponding Author
💜 Leaderboard (coming soon) |
💻 GitHub |
🤗 Hugging Face
📝 Project Page |
📰 Paper |
🎥 Video Demo
FiVE is a benchmark comprising 100 videos for… See the full description on the dataset page: https://huggingface.co/datasets/CiaranCw/FiVE-Fine-Grained-Video-Editing-Benchmark.Video-Editing-Dataset