The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

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…

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

✔（已完结）超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】

《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

AISystem 主要是指AI系统，包括AI芯片、AI编译器、AI推理和训练框架等AI全栈底层技术

Solve puzzles. Learn CUDA.

Book_4_《矩阵力量》 | 鸢尾花书：从加减乘除到机器学习；上架！

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接

A collection of pre-trained, state-of-the-art models in the ONNX format

李宏毅2021/2022/2023春季机器学习课程课件及作业

Material for gpu-mode lectures

This is the official code for MobileSAM project that makes SAM lightweight for mobile applications and beyond!

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse m…

A computer vision closed-loop learning platform where code can be run interactively online. 学习闭环《计算机视觉实战演练：算法与应用》中文电子书、源码、读者交流社区（持续更新中 ...） 📘 在线电子书 https://charmve.github.io/computer-vision-in-acti…

Efficient neural feature detector and descriptor

deeplearning.ai , By Andrew Ng, All slide and notebook + data + solutions and video link

A Modular Framework for 3D Gaussian Splatting and Beyond

Implementation of XFeat (CVPR 2024). Do you need robust and fast local feature extraction? You are in the right place!

BoT-SORT: Robust Associations Multi-Pedestrian Tracking

Coursera Open Courses from University of Toronto

A 3D Gaussian Splatting framework with various derived algorithms and an interactive web viewer

Code for "Efficient LoFTR: Semi-Dense Local Feature Matching with Sparse-Like Speed", CVPR 2024

Superpoint Implemented in PyTorch: https://arxiv.org/abs/1712.07629

[CVPR 2024 Oral] Rethinking Inductive Biases for Surface Normal Estimation

[CVPR 2024] LMDrive: Closed-Loop End-to-End Driving with Large Language Models

[AAAI 2025, Oral] DepthFM: Fast Monocular Depth Estimation with Flow Matching

Joint Deep Matcher for Points and Lines 🖼️💥🖼️ (ICCV 2023)