Stars
Code for "Single View Garment Reconstruction Using Diffusion Mapping Via Pattern Coordinates", SIGGRAPH2025
A monocular 3D pose estimation algorithm for humans and other animals
a comprehensive investigation of advanced physical aware AIGC works
About code release for "PhySense: Sensor Placement Optimization for Accurate Physics Sensing" (NeurIPS 2025 oral)
Official PyTorch implementation of One-Minute Video Generation with Test-Time Training
Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes [CVPR 2024]
Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey
[CVPR 2025] Official repository for "Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders"
A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
📷 Scripts for rendering Objaverse
About code release of "Transolver: A Fast Transformer Solver for PDEs on General Geometries", ICML 2024 Spotlight. https://arxiv.org/abs/2402.02366
[ECCV 2024] Neural Surface Detection for Unsigned Distance Fields
Surf-D: Generating High-Quality Surfaces of Arbitrary Topologies Using Diffusion Models (ECCV 2024)
High-Resolution 3D Assets Generation with Large Scale Hunyuan3D Diffusion Models.
Productive, portable, and performant GPU programming in Python.
Garment texture completion using custom fine tuned SD v1.5.
Pytorch Implementation (unofficial) of the paper "Mean Flows for One-step Generative Modeling" by Geng et al.
Official repo for PhysAvatar: Learning the Physics of Dressed 3D Avatars from Visual Observations, ECCV 2024
Repository for the CoRL 2024 paper: Cloth-Splatting: 3D Cloth State Estimation from RGB Supervision.
Inpaint anything using Segment Anything and inpainting models.
Code for "ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns", NeurIPS2023
[NeurIPS 2024] Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…