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Netflix/Vera-Layered-Video-Dataset

Netflix researchers released Vera, a layered diffusion model for content-preserving video editing, along with a dataset of over 18,000 video samples for training and evaluation. The model jointly generates an edit layer, alpha matte, and composite video to separate generated content from preserved elements. The Vera dataset includes background replacement and object addition edits across 49-frame and 81-frame sequences.

read2 min views1 publishedJul 9, 2026
Netflix/Vera-Layered-Video-Dataset
Image: Hugging Face Blog

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

Paper • 2606.23610 • Published • 11

Hongkai Zheng¹²* · Ta-Ying Cheng² · Benjamin Klein² · Yisong Yue² · 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.

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

Split Edit Type # Samples
train / 49-frames / realistic-set1-bg-change background_replace 914
train / 49-frames / realistic-set1-obj-add obj_add 470
train / 49-frames / realistic-set2-obj-add obj_add 770
train / 49-frames / synthetic-bg-change background_replace 4,994
train / 49-frames / synthetic-obj-add obj_add 4,848
49-Frame Train Total
11,996
Split Edit Type # Samples
train / 81-frames / realistic-set1-bg-change background_replace 457
train / 81-frames / realistic-set1-obj-add obj_add 235
train / 81-frames / realistic-set2-obj-add obj_add 385
train / 81-frames / synthetic-bg-change background_replace 2,497
train / 81-frames / synthetic-obj-add obj_add 2,431
81-Frame Train Total
6,005
Split Edit Type # Samples
test / bg-change background_replace 69
test / obj-add obj_add 72
Test Total
141
Source License

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

Source License
@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}
}
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