Stars
A comprehensive list of papers about Robot Manipulation, including papers, codes, and related websites.
[ICLR 2025] DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving
An orchestrated sub agent dev team powered by claude code
Very resourcefriendly and feature-rich replacement for i3status, written in pure Rust
A high-throughput and memory-efficient inference and serving engine for LLMs
[PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving
[CoRL '25] Pseudo-Simulation for Autonomous Driving; [NeurIPS '24] NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking
SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation
[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
OpenMMLab's next-generation platform for general 3D object detection.
Scalable Multi-Agent RL Training School for Autonomous Driving
Open-source Monocular Python HawkEye for Tennis
Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors
[IEEE T-PAMI 2024] All you need for End-to-end Autonomous Driving
BEHAVIOR-1K: a platform for accelerating Embodied AI research. Join our Discord for support: https://discord.gg/bccR5vGFEx
Example deep learning projects that use wandb's features.
Static reflection for enums (to string, from string, iteration) for modern C++, work with any enum type without any macro or boilerplate code
[NeurIPS 2023 Track Datasets and Benchmarks] OpenLane-V2: The First Perception and Reasoning Benchmark for Road Driving
[CoRL'22] PlanT: Explainable Planning Transformers via Object-Level Representations
[NeurIPS 2024 Datasets and Benchmarks Track] Closed-Loop E2E-AD Benchmark Enhanced by World Model RL Expert
PLUTO: Push the Limit of Imitation Learning-based Planning for Autonomous Driving
Visualizer for neural network, deep learning and machine learning models
Graph Neural Network Library for PyTorch
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion