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

SIMPL: A Simple and Efficient Multi-agent Motion Prediction Baseline for Autonomous Driving

Waymo Open Dataset

[CVPR 2024] SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction

[ICLR 2022] Official implementation of the paper "DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR"

[NeurIPS 2024] Behavioral Topology (BeTop), a multi-agent behavior formulation for interactive motion prediction and planning

MTR: Motion Transformer with Global Intention Localization and Local Movement Refinement, NeurIPS 2022.

[ICCV'2023] Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoders

[ICCV 2023 Oral] Game-theoretic modeling and learning of Transformer-based interactive prediction and planning

[CVPR 2023] Query-Centric Trajectory Prediction

Transformer: PyTorch Implementation of "Attention Is All You Need"

[IROS 2024] PP-TIL: Personalized Planning for Autonomous Driving with Instance-based Transfer Imitation Learning

[RSS 2023] Diffusion Policy Visuomotor Policy Learning via Action Diffusion

[ICCV 2023] VAD: Vectorized Scene Representation for Efficient Autonomous Driving

Introduction to the paper "Efficient Speed Planning for Autonomous Driving in Dynamic Environment with Interaction Point Model"

[ICRA'2024] Rethinking Imitation-based Planner for Autonomous Driving

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