Lately, Autonomous vehicles (AV) have been gaining traction globally owing to their huge
social, economic and environmental benefits. However, the rising safety apprehensions for …

The prediction of pedestrian behavior is essential for automated driving in urban traffic and
has attracted increasing attention in the vehicle industry. This task is challenging because …

We propose to predict the future trajectories of observed agents (eg, pedestrians or vehicles)
by estimating and using their goals at multiple time scales. We argue that the goal of a …

Predicting pedestrian movement is critical for human behavior analysis and also for safe and
efficient human-agent interactions. However, despite significant advancements, it is still …

Capturing high-dimensional social interactions and feasible futures is essential for
predicting trajectories. To address this complex nature, several attempts have been devoted …

Recent advances in trajectory prediction have shown that explicit reasoning about agents'
intent is important to accurately forecast their motion. However, the current research …

Predicting the trajectories of pedestrians in crowded conditions is an important task for
applications like autonomous navigation systems. Previous studies have tackled this …

Video anomaly detection (VAD) has been extensively studied for static cameras but is much
more challenging in egocentric driving videos where the scenes are extremely dynamic …

With rapid development in hardware (sensors and processors) and AI algorithms, automated
driving techniques have entered the public's daily life and achieved great success in …

Trajectory prediction is an essential task for successful human-robot interaction, such as in
autonomous driving. In this work, we address the problem of predicting future pedestrian …