Autonomous Driving
Showing 19 of 19 projects
An open-source, high-performance platform for developing, testing, and deploying autonomous vehicles.
An open-source simulator built on Unreal Engine for developing, training, and validating autonomous driving systems.
An open-source PyTorch toolbox for general 3D object detection, supporting LiDAR, camera, and multi-modal models.
A PyTorch-based toolbox for LiDAR-based 3D object detection, supporting multiple state-of-the-art models and datasets.
A PyTorch-based toolbox for LiDAR-based 3D object detection, supporting multiple state-of-the-art models and datasets.
A curated list of papers, datasets, and code for 3D point cloud analysis research, covering classification, segmentation, detection, and more.
A curated list of open-source tools for professional robotic development in C++ and Python, covering ROS, autonomous driving, and aerospace.
A collection of autonomous driving datasets and evaluation code for advancing machine perception and self-driving research.
A collection of minimalist Gymnasium environments for autonomous driving decision-making and reinforcement learning research.
A multi-sensor calibration toolbox for autonomous driving, supporting IMU, LiDAR, camera, and radar calibration.
A Python toolkit for working with the nuScenes and nuImages autonomous driving datasets, providing data loading, visualization, and evaluation utilities.
A comprehensive C++ toolkit for mobile robotics and computer vision research, providing libraries for SLAM, Bayesian filtering, and 3D geometry.
An unsupervised learning framework for depth and ego-motion estimation from monocular videos using TensorFlow.
A web-based labeling tool for creating semantic segmentation training data from 2D images and 3D point clouds.
A real-time Hybrid A* path planner for nonholonomic autonomous vehicles, generating smooth, efficient paths in unstructured environments.
A real-time baseline 3D multi-object tracking system using LiDAR point clouds, combining 3D Kalman filter and Hungarian algorithm.
A curated checklist of state-of-the-art research materials (datasets, papers, code) for interaction-aware trajectory prediction.
A deep learning pipeline for 3D object detection from RGB-D data by combining 2D detectors with PointNet-based 3D processing.
A general-purpose PyTorch codebase for 3D object detection with state-of-the-art model implementations and multi-dataset support.
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