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Dataset for Vera: A Layered Diffusion Model for Content-Preserving Video Editing
Hongkai Zheng¹²* ·<br>Ta-Ying Cheng² ·<br>Benjamin Klein² ·<br>Yisong Yue² ·<br>Zhuoning Yuan²†
¹California Institute of Technology ²Netflix, Inc.
*Work done during an internship at Netflix †Project Lead
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.
📋 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.
Split<br>Edit Type<br># Samples
train / 49-frames / realistic-set1-bg-change<br>background_replace<br>914
train / 49-frames / realistic-set1-obj-add<br>obj_add<br>470
train / 49-frames / realistic-set2-obj-add<br>obj_add<br>770
train / 49-frames / synthetic-bg-change<br>background_replace<br>4,994
train / 49-frames / synthetic-obj-add<br>obj_add<br>4,848
49-Frame Train Total
11,996
🎞️ Splits — 81 Frames (5 sec)
Split<br>Edit Type<br># Samples
train / 81-frames / realistic-set1-bg-change<br>background_replace<br>457
train / 81-frames / realistic-set1-obj-add<br>obj_add<br>235
train / 81-frames / realistic-set2-obj-add<br>obj_add<br>385
train / 81-frames / synthetic-bg-change<br>background_replace<br>2,497
train / 81-frames / synthetic-obj-add<br>obj_add<br>2,431
81-Frame Train Total
6,005
🧪 Test Splits
Split<br>Edit Type<br># Samples
test / bg-change<br>background_replace<br>69
test / obj-add<br>obj_add<br>72
Test Total
141
🗂️ Data Sources
🏋️ Training Set
Source<br>License
Pexels<br>Pexels License
Mixkit<br>Mixkit License
VideoMatte240K<br>MIT License
🧪 Test Set
The test set is sourced from the training sources above, plus:
Source<br>License
DAVIS<br>CC BY-NC 4.0
VACEBench<br>Apache License 2.0
📝 Citation
@article{zheng2026vera,<br>title = {Vera: A Layered Diffusion Model for Content-Preserving Video Editing},<br>author = {Zheng, Hongkai and Cheng, Ta-Ying and Klein, Benjamin and Yue, Yisong and Yuan, Zhuoning},<br>journal = {arXiv preprint arXiv:2606.23610},<br>year = {2026}
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Paper for netflix/Vera-Layered-Video-Dataset<br>Paper • 2606.23610 • Published 18 days ago • 11