Vista4D: Video Reshooting with 4D Point Clouds (CVPR 2026 Highlight) – Model Checkpoints
Kuan Heng Lin1,3∗, Zhizheng Liu1,4∗, Pablo Salamanca1,2, Yash Kant1,2, Ryan Burgert1,2,5∗, Yuancheng Xu1,2, Koichi Namekata1,2,6∗, Yiwei Zhao2, Bolei Zhou4, Micah Goldblum3, Paul Debevec1,2, Ning Yu1,2
1Eyeline Labs, 2Netflix, 3Columbia University, 4UCLA, 5Stony Brook University, 6University of Oxford
∗Work done during an internship at Eyeline Labs
Vista4D is a video reshooting framework which synthesizes the dynamic scene represented by an input source video from novel camera trajectories and viewpoints. We bridge the distribution shift between training and inference for point-cloud-grounded video reshooting, as Vista4D is robust to point cloud artifacts from imprecise 4D reconstruction of real-world videos by training on noisy, reconstructed multiview videos. Our 4D point cloud with temporally-persistent static points also explicitly preserves scene content and improved camera control. Vista4D generalizes to real-world applications such as dynamic scene expansion (casual video capture of scene as background reference), 4D scene recomposition (point cloud editing), and long video inference with memory.
This is the Hugging Face repository containing our model weights. We provide two Vista4D checkpoints finetuned on Wan-AI/Wan2.1-T2V-14B(https://huggingface.co/Wan-AI/Wan2.1-T2V-14B):
| Checkpoint | Base model | Training resolution | Training steps | Notes |
|---|---|---|---|---|
384p49_step=30000 |
Wan2.1-T2V-14B |
672 × 384, 49 frames | 30000 | N/A |
720p49_step=3000 |
Wan2.1-T2V-14B |
1280 × 720, 49 frames | 3000 | Finetuned from 384p49_step=30000 |
To do Vista4D inference, first download the Wan 2.1 and Vista4D checkpoints to ./checkpoints/. The Vista4D checkpoints are hosted on Eyeline-Labs/Vista4D. Download both the 384p and 720p checkpoints into ./checkpoints/vista4d/ with
hf download Eyeline-Labs/Vista4D --local-dir ./checkpoints/vista4d
If you only need one resolution, pass --include to grab just that variant with
hf download Eyeline-Labs/Vista4D --local-dir ./checkpoints/vista4d --include "384p49_step=30000/*" OR "720p49_step=3000/*"
You'll also need the Wan2.1-T2V-14B base model. Download it from Wan-AI/Wan2.1-T2V-14B into ./checkpoints/wan/Wan2.1-T2V-14B/ with
hf download Wan-AI/Wan2.1-T2V-14B --local-dir ./checkpoints/wan/Wan2.1-T2V-14B
Instructions on how to use these weights, more results, and paper can be found on our project page and GitHub repository.