Trajectory Prediction

Trajectory Prediction is the problem of predicting the short-term (1-3 seconds) and long-term (3-5 seconds) spatial coordinates of various road-agents such as cars, buses, pedestrians, rickshaws, and animals, etc. These road-agents have different dynamic behaviors that may correspond to aggressive or conservative driving styles. Source: Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs

Benchmarks

Libraries

Datasets

Subtasks

Most implemented papers

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

Content

GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving

Trajectron++: Dynamically-Feasible Trajectory Forecasting with Heterogeneous Data

TNT: Target-driveN Trajectory Prediction

From Recognition to Prediction: Analysis of Human Action and Trajectory Prediction in Video

Social NCE: Contrastive Learning of Socially-aware Motion Representations

DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents

Convolutional Social Pooling for Vehicle Trajectory Prediction

Unsupervised Traffic Accident Detection in First-Person Videos

It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction