Recognizing human activities from video sequences or still images is a challenging task due
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …

As mobile robots are increasingly introduced into our daily lives, it grows ever more
imperative that these robots navigate with and among people in a safe and socially …

Pedestrian trajectory prediction is a key technology in autopilot, which remains to be very
challenging due to complex interactions between pedestrians. However, previous works …

Human trajectory prediction is challenging and critical in various applications (eg,
autonomous vehicles and social robots). Because of the continuity and foresight of the …

Human trajectory forecasting is an inherently multimodal problem. Uncertainty in future
trajectories stems from two sources:(a) sources that are known to the agent but unknown to …

Human trajectory forecasting with multiple socially interacting agents is of critical importance
for autonomous navigation in human environments, eg, for self-driving cars and social …

Standardized benchmarks have been crucial in pushing the performance of computer vision
algorithms, especially since the advent of deep learning. Although leaderboards should not …

Since the past few decades, human trajectory forecasting has been a field of active research
owing to its numerous real-world applications: evacuation situation analysis, deployment of …

Predicting the future trajectories of multiple interacting pedestrians in a scene has become
an increasingly important problem for many different applications ranging from control of …

This paper addresses the problem of path prediction for multiple interacting agents in a
scene, which is a crucial step for many autonomous platforms such as self-driving cars and …