yuzewang1998
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A web-based 3D visualization tool for 3D computer vision.
A VR viewer for gaussian splatting models developped as native plugin for unity with the original CUDA rasterizer.
[ECCV 2024] SplatFields: Neural Gaussian Splats for Sparse 3D and 4D Reconstruction
[ECCV 2024] The official code of paper "Open-Vocabulary SAM".
Pytorch Code for "LEGaussians: Language Embedded 3D Gaussians for Open-Vocabulary Scene Understanding"
[SIGGRAPH Asia 2024 (Journal Track)] StableNormal: Reducing Diffusion Variance for Stable and Sharp Normal
Official implementation of the paper "LangSplat: 3D Language Gaussian Splatting" [CVPR2024 Highlight]
[NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"
ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model
Reproducible evaluation of NeRF and 3DGS methods
Feature splatting based on INRIA GS rasterizer
This is the official repo for PyTorch implementation of paper "ClimateNeRF: Extreme Weather Synthesis in Neural Radiance Field", ICCV 2023.
Official implementation of the paper "GOI: Find 3D Gaussians of Interest with an Optimizable Open-vocabulary Semantic-space Hyperplane"(ACM MM2024).
Full python interactive 3D Gaussian Splatting viewer for real-time editing and analyzing.
WildGaussians: 3D Gaussian Splatting In the Wild
[ECCV 2024] Efficient Large-Baseline Radiance Fields, a feed-forward 2DGS model
Official Pytorch implementation of the preprint paper "Castle in the Sky: Dynamic Sky Replacement and Harmonization in Videos", in arXiv:2010.11800.
Source code of paper "NVS-Solver: Video Diffusion Model as Zero-Shot Novel View Synthesizer"
[CVPR 2024 Highlight] Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields
3D Gaussian Splatting adapted version of OmniSeg3D (CVPR2024)
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
Official code for "Neural Gaffer: Relighting Any Object via Diffusion"
Open-source and strong foundation image recognition models.