[ICCV'23] Hidden Biases of End-to-End Driving Models

Implementation of π₀, the robotic foundation model architecture proposed by Physical Intelligence

RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation

Scalable Urban Dynamic Scenes

PyTorch code for the paper "Model-Based Imitation Learning for Urban Driving".

ML Dataset Governance Policy for Autonomous Vehicle Datasets

Visualization Library

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Code for Paper, MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D Queries. https://tsinghua-mars-lab.github.io/mutr3d/

[ECCV2022] PETR: Position Embedding Transformation for Multi-View 3D Object Detection

[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.

Code for paper: FUTR3D: a unified sensor fusion framework for 3d detection

Pytorch package to compute Chamfer distance between point sets (pointclouds).

The devkit of the nuScenes dataset.

Deformable DETR: Deformable Transformers for End-to-End Object Detection.

End-to-End Object Detection with Transformers

PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722