Collaborative perception in automated vehicles leverages the exchange of information
between agents aiming to elevate perception results. Previous camera-based collaborative …

Multi-person motion prediction is a challenging problem due to the dependency of motion on
both individual past movements and interactions with other people. Transformer-based …

Vision-based Bird's Eye View (BEV) representation is an emerging perception formulation
for autonomous driving. The core challenge is to construct BEV space with multi-camera …

Abstract Bird's-eye View (BeV) representations have emerged as the de-facto shared space
in driving applications offering a unified space for sensor data fusion and supporting various …

In autonomous driving behavior prediction is fundamental for safe motion planning hence
the security and robustness of prediction models against adversarial attacks are of …

With the increasing popularity of autonomous driving based on the powerful and unified
bird's-eye-view (BEV) representation, a demand for high-quality and large-scale multi-view …

Pedestrian trajectory prediction is a classic and challenging scientific task that involves
complex engineering science and human factors. These challenges have spurred a …

Learning the dense bird's eye view (BEV) motion flow in a self-supervised manner is an
emerging research for robotics and autonomous driving. Current self-supervised methods …

For safe motion planning in real-world autonomous vehicles require behavior prediction
models that are reliable and robust to distribution shifts. The recent studies suggest that the …

Predicting the future occupancy states of the surrounding environment is a vital task for
autonomous driving. However current best-performing single-modality methods or multi …