A Generalizable World Model for Autonomous Driving

BEVFormer, UniAD, VAD in CARLA under Closed-Loop Evaluation

Closed-loop multi-ability evaluation of end-to-end autonomous driving algorithms

[ECCV 2024] 3D World Model for Autonomous Driving

World Model based Autonomous Driving Platform in CARLA 🚗

Mastering Diverse Domains through World Models

[CVPR 2024] A world model for autonomous driving.

A computationally efficient and robust LiDAR-inertial odometry (LIO) package

An operating system, but it only plays Tetris.

Custom 16-bit homebrew CPU, emulator, renderer, circuit, and language

SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation

[ICCV 2023 Oral] A New Paradigm for End-to-end Autonomous Driving to Alleviate Causal Confusion

[ECCV 2022] ST-P3, an end-to-end vision-based autonomous driving framework via spatial-temporal feature learning.

Code for paper "MapTracker: Tracking with Strided Memory Fusion for Consistent Vector HD Mapping", ECCV 2024 (Oral)

[ECCV 2024] This is the official implementation of MapQR, an end-to-end method with an emphasis on enhancing query capabilities for constructing online vectorized maps.

The repo for "Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image" and "Metric3Dv2: A Versatile Monocular Geometric Foundation Model..."

[CVPR 2024 Highlight] Visual Point Cloud Forecasting

PyTorch code and models for V-JEPA self-supervised learning from video.

PyTorch implementation for the paper "Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving"

[ECCV 2024 Oral] DriveLM: Driving with Graph Visual Question Answering

A comprehensive survey of forging vision foundation models for autonomous driving, including challenges, methodologies, and opportunities.

[CVPR 2024 Highlight] GenAD: Generalized Predictive Model for Autonomous Driving & Foundation Models in Autonomous System

A simple method for finding the extrinsic calibration between a 3D lidar and a 6-dof pose sensor

3D Occupancy Prediction Benchmark in Autonomous Driving

The electronic structure package for quantum computers.

Making large AI models cheaper, faster and more accessible

Official implementation of paper "Cumulative Reasoning With Large Language Models" (https://arxiv.org/abs/2308.04371)

[ECCV 2024] DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.