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Official code, models, and data for Vista4D: Video Reshooting with 4D Point Clouds (CVPR 2026 Highlight)
| Date | Stars |
|---|---|
| 2026-07-24 | 559 |
| 2026-07-25 | 560 |
| 2026-07-28 | 563 |
| 2026-07-30 | 563 |
| 2026-08-06 | 563 |
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# Vista4D: Video Reshooting with 4D Point Clouds (CVPR 2026 Highlight) [](https://eyeline-labs.github.io/Vista4D) [](https://arxiv.org/abs/2604.21915) [](https://huggingface.co/Eyeline-Labs/Vista4D) [](https://huggingface.co/datasets/Eyeline-Labs/Vista4D-Eval-Data) [Kuan Heng Lin](https://kuanhenglin.github.io)<sup>1,3∗</sup>, [Zhizheng Liu](https://bosmallear.github.io)<sup>1,4∗</sup>, [Pablo Salamanca](https://pablosalaman.ca)<sup>1,2</sup>, [Yash Kant](https://yashkant.github.io)<sup>1,2</sup>, [Ryan Burgert](https://ryanndagreat.github.io)<sup>1,2,5∗</sup>, [Yuancheng Xu](https://yuancheng-xu.github.io)<sup>1,2</sup>, [Koichi Namekata](https://kmcode1.github.io)<sup>1,2,6∗</sup>, [Yiwei Zhao](https://zhaoyw007.github.io)<sup>2</sup>, [Bolei Zhou](https://boleizhou.github.io)<sup>4</sup>, [Micah Goldblum](https://goldblum.github.io)<sup>3</sup>, [Paul Debevec](https://www.pauldebevec.com)<sup>1,2</sup>, [Ning Yu](https://ningyu1991.github.io)<sup>1,2</sup> <br/> <sup>1</sup>Eyeline Labs, <sup>2</sup>Netflix, <sup>3</sup>Columbia University, <sup>4</sup>UCLA, <sup>5</sup>Stony Brook University, <sup>6</sup>University of Oxford<br> <sup>∗</sup>*Work done during an internship at Eyeline Labs* # 🗣 Updates - **2026/05/02:** [WanGP](https://github.com/deepbeepmeep/Wan2GP) v11.52 has added Vista4D to their repo! Check it out if you want to run Vista4D with lower VRAM and optionally fewer timesteps 🏎💨 - **2026/04/23:** Vista4D inference code, model weights, and evaluation dataset 🖥 have been released! - **2026/04/09:** Vista4D has been selected as a Highlight paper ✨ - **2026/02/21:** Vista4D has been accepted to CVPR 2026 🎉 # 👀 Overview  **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 repository contains the following: - [Inference code for Vista4D for video reshooting](#vista4d-code) - [Instructions to download and use our model weights](#wan-21-and-vista4d-checkpoints) - [Instructions to run Vista4D on our evaluation dataset](#evaluation-dataset-and-inference) - [Inference code (and UI) for 4D scene recomposition (point cloud editing)](#application-4d-scene-recomposition-point-cloud-editing) - [Inference code for dynamic scene expansion](#application-dynamic-scene-expansion-dse) - [Our camera UI, for all of the above (video reshooting *and* all applications!)](#camera-ui-optiona
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