No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

Human behavior has the nature of indeterminacy, which requires the pedestrian trajectory
prediction system to model the multi-modality of future motion states. Unlike existing …

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 …

Predicting the future behavior of agents is a fundamental task in autonomous vehicle
domains. Accurate prediction relies on comprehending the surrounding map, which …

Learning behavioral patterns from observational data has been a de-facto approach to
motion forecasting. Yet, the current paradigm suffers from two shortcomings: brittle under …

Volumetric video (VV) recently emerges as a new form of video application providing a
photorealistic immersive 3D viewing experience with 6 degree-of-freedom (DoF), which …

Predicting the trajectories of road agents is fundamental for self-driving cars. Trajectory
prediction contains many sources of uncertainty in data and modelling. A thorough …

We present a new large dataset of indoor human and robot navigation and interaction,
called THÖR-MAGNI, that is designed to facilitate research on social human navigation: for …

Explaining the decision made by end-to-end autonomous driving is a difficult task. These
approaches take raw sensor data and compute the decision as a black box with large deep …

Accurate trajectory prediction is essential for safe and efficient autonomous driving in
complex traffic environments. While artificial intelligence has shown great promise in …