Stars
Template-based Novel Object Detection and Segmentation
PyTorch code and models for the DINOv2 self-supervised learning method.
[CVPR 2024] PyTorch implementation of GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondence
Python toolkit for the BOP benchmark: evaluation and utilities for 6D object pose estimation.
A detailed formulae explanation on gaussian splatting
[CVPR 2025] Any6D: Model-free 6D Pose Estimation of Novel Objects
Code for "CosyPose: Consistent multi-view multi-object 6D pose estimation", ECCV 2020.
Awesome work on object 6 DoF pose estimation
[CVPR2024] Code for "SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose Estimation".
[CVPR 2024 Highlight] FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects
[ICCV 2023 R6D] PyTorch implementation of CNOS: A Strong Baseline for CAD-based Novel Object Segmentation based on Segmenting Anything and DINOv2
Code for "MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare", CoRL 2022.
Lisp code for the textbook "Paradigms of Artificial Intelligence Programming"
FoundPose: Unseen Object Pose Estimation with Foundation Features, ECCV 2024
Scenarios, tutorials and demos for Autonomous Driving
End-to-End Learning from Human and Autopilot Driving
Project on getting the angle of steering rotation in a self-driving car. This project is inspired by NVIDIA End to End Learning for Self-Driving Cars and data is gathered from Udacity's Behavioral …
A simple self-driving car module for humans 🚘 🛣️
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
Machine learning and deep learning resources
Awesome free machine learning and AI courses with video lectures.
🎓 Gebze Technical University - Computer Engineering Notes and Assignments
Collection of resources spanning key areas of Computer Science
A curated list of awesome computer vision resources
Master programming by recreating your favorite technologies from scratch.
A compiler that accepts any valid program written in C. It is made using Lex and Yacc. Returns a symbol table, parse tree, annotated syntax tree and intermediate code.
A collection of algorithms and data structures