Stars
High-Resolution 3D Assets Generation with Large Scale Hunyuan3D Diffusion Models.
The official implementation of "CityDreamer4D: Compositional Generative Model of Unbounded 4D Cities". (arXiv 2501.08983)
Real-time dense scene reconstruction with SLAM3R
Code release for https://kovenyu.com/WonderWorld/
The first behavioral foundation model to control a virtual physics-based humanoid agent for a wide range of whole-body tasks.
[CVPR'24] Aerial Lifting: Neural Urban Semantic and Building Instance Lifting from Aerial Imagery
🐍 Geometric Computer Vision Library for Spatial AI
You See it, You Got it: Learning 3D Creation on Pose-Free Videos at Scale
[CVPR2024 (Highlight)] RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D. Live Demo：https://modelscope.cn/studios/Damo_XR_Lab/3D_AIGC
Official repo for paper "Structured 3D Latents for Scalable and Versatile 3D Generation".
[ICLR 2025] EdgeRunner: Auto-regressive Auto-encoder for Efficient Mesh Generation
From Face to Natural Image: Learning Real Degradation for Blind Image Super-Resolution (ECCV 2022)
This is a totally reimplemented version of our ASFFNet (CVPR2020) on 512*512 images.
Learning Dual Memory Dictionaries for Blind Face Restoration
Blind Face Restoration via Deep Multi-scale Component Dictionaries (ECCV 2020)
Learning Generative Structure Prior for Blind Text Image Super-resolution [CVPR 2023]
Official repository for "SAR3D: Autoregressive 3D Object Generation and Understanding via Multi-scale 3D VQVAE"
High-quality and editable surfel 3D Gaussian generation through native 3D diffusion (ICLR 2025)
Event-3DGS: Event-based 3D Reconstruction Using 3D Gaussian Splatting
[NeurIPS'2024] Neural Signed Distance Function Inference through Splatting 3D Gaussians Pulled on Zero-Level Set
Lightweight Python framework that provides a high-level API for creating and rendering scenes with Blender.
[CVPR 2024] Official Implementation of the paper "CAGE: Controllable Articulation GEneration"