Popular GitHub Repositories for Trajectory

A selection of state-of-the-art research materials on trajectory prediction

Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution).

[CVPR 2023] Query-Centric Trajectory Prediction

The ApolloScape Open Dataset for Autonomous Driving and its Application.

Trajectory Planner in Multi-Agent and Dynamic Environments

Code for "Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction" CVPR 2020

Solution for Waymo Motion Prediction Challenge 2022. Our implementation of MultiPath++

Code for "Transformer Networks for Trajectory Forecasting"

A PyTorch implementation of ACM SIGKDD 2019 paper "Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks"

A Unified Framework for scalable Vehicle Trajectory Prediction, ECCV 2024

Code for "Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text" (NeurIPS 2024).

A differentiable physics engine for robotics

Official Repository of the paper "Trajectory Consistency Distillation"

Deep Learning for Vision-based Prediction

A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

Online RL with Simple Reward Enables Training VLA Models with Only One Trajectory

[ICCV 2021] Official PyTorch Implementation of "AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting".

Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”

Official implementation for the paper "Model-based Diffusion for Trajectory Optimization". Model-based diffusion (MBD) is a novel diffusion-based trajectory optimization framework that employs a dynamics model to run the reverse denoising process to generate high-quality trajectories.

Summary of open source code for deep learning models in the field of traffic prediction