Trajectory Forecasting

28 papers with code • 3 benchmarks • 6 datasets

Trajectory forecasting is a sequential prediction task, where a forecasting model predicts future trajectories of all moving agents (humans, vehicles, etc.) in a scene, based on their past trajectories and/or the scene context.

(Illustrative figure from Social NCE: Contrastive Learning of Socially-aware Motion Representations)

Greatest papers with code

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

agrimgupta92/sgan CVPR 2018

Understanding human motion behavior is critical for autonomous moving platforms (like self-driving cars and social robots) if they are to navigate human-centric environments.

Motion Forecasting Multi-future Trajectory Prediction +2

Argoverse: 3D Tracking and Forecasting with Rich Maps

argoai/argoverse-api CVPR 2019

In our baseline experiments, we illustrate how detailed map information such as lane direction, driveable area, and ground height improves the accuracy of 3D object tracking and motion forecasting.

3D Object Tracking Autonomous Vehicles +3

OpenTraj: Assessing Prediction Complexity in Human Trajectories Datasets

crowdbotp/OpenTraj 2 Oct 2020

Human Trajectory Prediction (HTP) has gained much momentum in the last years and many solutions have been proposed to solve it.

Self-Driving Cars Trajectory Forecasting

Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models

vincent-leguen/STDL NeurIPS 2019

We introduce a differentiable loss function suitable for training deep neural nets, and provide a custom back-prop implementation for speeding up optimization.

Dynamic Time Warping Time Series +2

The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction

JunweiLiang/Multiverse CVPR 2020

The first contribution is a new dataset, created in a realistic 3D simulator, which is based on real world trajectory data, and then extrapolated by human annotators to achieve different latent goals.

Autonomous Driving Human motion prediction +4

Transformer Networks for Trajectory Forecasting

FGiuliari/Trajectory-Transformer 18 Mar 2020

In particular, the TF model without bells and whistles yields the best score on the largest and most challenging trajectory forecasting benchmark of TrajNet.

Trajectory Forecasting

Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs

amiryanj/socialways CVPR 2019

We show through experiments on real and synthetic data that the proposed method leads to generate more diverse samples and to preserve the modes of the predictive distribution.

Human motion prediction Multi-future Trajectory Prediction +3