清华大学 邓俊辉 数据结构 C++版本 第三版 教材配套代码整理

Code for our Siggraph 24 Paper Differentiable Geodesic Distance for Intrinsic Minimization on Triangle Meshes

EPFL Course - Optimization for Machine Learning - CS-439

Official implementation of Stochastic Taylor Derivative Estimator (STDE) NeurIPS2024

Machine Learning Resources, Practice and Research

Train transformer language models with reinforcement learning.

Flash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single Image

This repo contains the projects: 'Virtual Normal', 'DiverseDepth', and '3D Scene Shape'. They aim to solve the monocular depth estimation, 3D scene reconstruction from single image problems.

Official python implementation for ICML 2024: "Learning Solution-Aware Transformers for Efficiently Solving Quadratic Assignment Problem"

PyTorch code for our NeurIPS 2023 paper "Hierarchical Integration Diffusion Model for Realistic Image Deblurring"

PyTorch code for our NeurIPS 2022 paper "Cross Aggregation Transformer for Image Restoration"

PyTorch code for our ICCV 2023 paper "Dual Aggregation Transformer for Image Super-Resolution"

[NeurIPS 2023 Spotlight] This project is the official implementation of our accepted NeurIPS 2023 (spotlight) paper QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution.

SwinIR: Image Restoration Using Swin Transformer (official repository)

CVPR2024 - Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary

[ECCV 2024 - Oral] HiT-SR: Hierarchical Transformer for Efficient Image Super-Resolution

High-Resolution Image Synthesis with Latent Diffusion Models

[CVPR 2024] X-Adapter: Adding Universal Compatibility of Plugins for Upgraded Diffusion Model

[ICCV 2023] Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation

[SIGGRAPH2024] DreamMat: High-quality PBR Material Generation with Geometry- and Light-aware Diffusion Models

Official repo for consistency models.

[ICCV 2021] Our work presents a novel neural rendering approach that can efficiently reconstruct geometric and neural radiance fields for view synthesis.

[ECCV'2024] Gaussian Grouping for open-world Anything reconstruction, segmentation and editing.

Graph Machine Learning course, Xavier Bresson, 2023

Navigating Spreading-out Graph For Approximate Nearest Neighbor Search

[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering

[CVPR 2024] Text-to-3D using Gaussian Splatting

Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"

A resource repository for 3D machine learning