video editing
Total_Editing_Synthetic_Video_Albedo_FullFiVE-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
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💻 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.Generic-Instructional-Video-Editing-Challenge-DatasetVideo-InContext-Editing