Motion Forecasting

17 papers with code • 1 benchmarks • 3 datasets

Motion forecasting is the task of predicting the location of a tracked object in the future

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

Peeking into the Future: Predicting Future Person Activities and Locations in Videos

google/next-prediction CVPR 2019

To facilitate the training, the network is learned with an auxiliary task of predicting future location in which the activity will happen.

Future prediction Human motion prediction +4

Learning Lane Graph Representations for Motion Forecasting

uber-research/LaneGCN ECCV 2020

We propose a motion forecasting model that exploits a novel structured map representation as well as actor-map interactions.

Motion Forecasting Trajectory Prediction

DenseTNT: End-to-end Trajectory Prediction from Dense Goal Sets

Tsinghua-MARS-Lab/DenseTNT ICCV 2021

In this work, we propose an anchor-free and end-to-end trajectory prediction model, named DenseTNT, that directly outputs a set of trajectories from dense goal candidates.

Motion Forecasting motion prediction +1

The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal Graphs

StanfordASL/Trajectron ICCV 2019

Developing safe human-robot interaction systems is a necessary step towards the widespread integration of autonomous agents in society.

Decision Making Human robot interaction +3

Social NCE: Contrastive Learning of Socially-aware Motion Representations

vita-epfl/social-nce-crowdnav ICCV 2021

Learning socially-aware motion representations is at the core of recent advances in multi-agent problems, such as human motion forecasting and robot navigation in crowds.

Autonomous Navigation Motion Forecasting +1

Trajectory Prediction with Graph-based Dual-scale Context Fusion

hkust-aerial-robotics/dsp 2 Nov 2021

In this paper, we present a graph-based trajectory prediction network named the Dual Scale Predictor (DSP), which encodes both the static and dynamical driving context in a hierarchical manner.

Motion Forecasting motion prediction +1