Lists (1)
Stars
This repository contains the implementation of Ground4Act, a two-stage approach for collaborative pushing and grasping in clutter using a visual-language model.
An ultra-lightweight and blazing-fast Messaging broker/bus for IoT edge & SDV
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
An educational resource to help anyone learn deep reinforcement learning.
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
An elegant PyTorch deep reinforcement learning library.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
[ECCV 2022] ST-P3, an end-to-end vision-based autonomous driving framework via spatial-temporal feature learning.
(ICCV 2021, Oral) RL and distillation in CARLA using a factorized world model
This repo is the official implementation of "BEVTrack: A Simple and Strong Baseline for 3D Single Object Tracking in Bird's-Eye View".
A collection of recent resources on End-to-End Autonomous Driving [survey accepted in IEEE TIV]
Official implementation of "Task-Induced Representation Learning", Yamada et al., ICLR 2022
Implementation code for: End-to-end Autonomous Driving with Semantic Depth Cloud Mapping and Multi-agent, IEEE Trans. Intelligent Vehicles, 2022.
[CVPR 2023 Best Paper Award] Planning-oriented Autonomous Driving
[ICLR 2023] Pytorch implementation of PPGeo, a fully self-supervised driving policy pre-training framework to learn from unlabeled driving videos.
[IEEE T-PAMI] All you need for End-to-end Autonomous Driving
A curated list of awesome End-to-End Autonomous Driving resources (continually updated)
[ICCV'23] Hidden Biases of End-to-End Driving Models
"Learning by Cheating" (CoRL 2019) submission for the 2020 CARLA Challenge
The source code for the blog post The 37 Implementation Details of Proximal Policy Optimization
Code for the paper "Reinforced Curriculum Learning for Autonomous Driving in CARLA" (ICIP 2021)
Repository to store conditional imitation learning based AI that runs on CARLA.
[IEEE T-PAMI] Awesome BEV perception research and cookbook for all level audience in autonomous diriving
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/
Official code and checkpoint release for mobile robot foundation models: GNM, ViNT, and NoMaD.
[CVPR 2023] Pytorch implementation of ThinkTwice, a SOTA Decoder for End-to-end Autonomous Driving under BEV.
(CoRL 2019) Driving in CARLA using waypoint prediction and two-stage imitation learning