3AFamily/Vera-Layered-Video-Dataset

Dataset for Vera: A Layered Diffusion Model for Content-Preserving Video Editing

<p align="left"> <a href="https://devzhk.github.io/">Hongkai Zheng</a>¹²* &nbsp;&middot;&nbsp; <a href="https://ttchengab.github.io/">Ta-Ying Cheng</a>² &nbsp;&middot;&nbsp; <a href="https://scholar.google.com/citations?user=xkX9W9QAAAAJ&hl=en">Benjamin Klein</a>² &nbsp;&middot;&nbsp; <a href="https://yisongyue.com/">Yisong Yue</a>² &nbsp;&middot;&nbsp; <a href="https://zhuoning.cc/">Zhuoning Yuan</a>²† </p>

<p align="left"> ¹California Institute of Technology &nbsp;&nbsp; ²Netflix, Inc.<br> _{*Work done during an internship at Netflix &nbsp; †Project Lead} </p>

<p align="left"> <a href="https://vera-layered-diffusion.github.io/"><img src="https://img.shields.io/badge/🌐-Project%20Page-blue" alt="Project Page"></a> <a href="https://arxiv.org/abs/2606.23610"><img src="https://img.shields.io/badge/arXiv-Paper-b31b1b?logo=arxiv&logoColor=white" alt="Paper"></a> <a href="https://huggingface.co/datasets/netflix/Vera-Layered-Video-Dataset"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Dataset-ff9d00" alt="Dataset"></a> <a href="#"><img src="https://img.shields.io/badge/License-Apache%202.0-green.svg" alt="License"></a> </p>

TL;DR: A layered diffusion framework for video editing. Vera jointly generates an edit layer, an alpha matte, and a composite video, separating what to generate from what to preserve. Disclaimer: This is a research prototype, not an official product.

<p align="left"> <video src="https://vera-layered-diffusion.github.io/assets/videos/vera-promo-video-v5-0.7x.mp4" width="50%" controls autoplay loop muted playsinline></video> </p>

📋 Dataset Description

• —Curated by: Hongkai Zheng, Ta-Ying Cheng, Benjamin Klein, Yisong Yue, Zhuoning Yuan
• —License: Apache License 2.0
• —Paper: Vera: A Layered Diffusion Model for Content-Preserving Video Editing

📦 Dataset Structure

🎞️ Splits — 49 Frames (3 sec)

Note: The current Vera models are trained on 49-frame sequences.

🎞️ Splits — 81 Frames (5 sec)

🧪 Test Splits

🗂️ Data Sources

🏋️ Training Set

🧪 Test Set

The test set is sourced from the training sources above, plus:

📝 Citation

@article{zheng2026vera,
    title     = {Vera: A Layered Diffusion Model for Content-Preserving Video Editing},
    author    = {Zheng, Hongkai and Cheng, Ta-Ying and Klein, Benjamin and Yue, Yisong and Yuan, Zhuoning},
    journal   = {arXiv preprint arXiv:2606.23610},
    year      = {2026}
}