Rain's repositories
CARLA_INVS
multi-agent data collection and distributed learning in CARLA simulation
AirSim
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
AnomalyGPT
[AAAI 2024 Oral] AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models
carla
Open-source simulator for autonomous driving research.
carla_dataset_tools
Tools for dataset generation based on CARLA simulator.
DAFormer
[CVPR22] Official Implementation of DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
DriveLikeAHuman
Drive Like a Human: Rethinking Autonomous Driving with Large Language Models
kaggle-solutions
🏅 Collection of Kaggle Solutions and Ideas 🏅
kdbai-samples
Developer samples for the KDB.AI vector database
kitti_object_vis
KITTI Object Visualization (Birdview, Volumetric LiDar point cloud )
Lidar_For_AD_references
A list of references on lidar point cloud processing for autonomous driving
MARL_CAVs
Multi-agent Reinforcement Learning for Autonomous Vehicles
OpenCDA
A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.
OpenCOOD
An opensource framework for cooperative detection
PascalVOC-to-Images
A small tool to cut images from Pascal VOC datasets
readpaper
This repository serves as a centralized collection for articles pertaining to various topics such as Domain adaptation, transfer learning, and prompt learning. The repository also includes links to my reading notes for each paper.Feel free to visit my personal homepage and contact me for collaboration and discussion.
slambook2
edition 2 of the slambook
stable-diffusion
A latent text-to-image diffusion model
sumosim
A sumo based simulator that can support both micro and macro level control
SUSTechPOINTS
3D Point Cloud Annotation Platform for Autonomous Driving
U-2-Net
The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
YOLOP
You Only Look Once for Panopitic Driving Perception.（https://arxiv.org/abs/2108.11250）