Holistic driving scene understanding is a critical step toward intelligent transportation
systems. It involves different levels of analysis, interpretation, reasoning and decision …

Traffic scene understanding involves the perception and accurate representation of a
vehicles surroundings within a comprehensive environment model. Generally, automotive …

Recently, beyond object detection and segmentation, high-level understanding of
autonomous driving scenarios is attracting increasing attention. And traffic scene graph has …

The driving behavior at urban intersections is very complex. It is thus crucial for autonomous
vehicles to comprehensively understand challenging urban traffic scenes in order to …

Driving scene understanding is to obtain compre-hensive scene information through the
sensor data and provide a basis for downstream tasks, which is indispensable for the safety …

Scene understanding plays a crucial role in autonomous driving by utilizing sensory data for
contextual information extraction and decision making. Beyond modeling advances, the …

This study addresses the problem of holistic road scene understanding based on the
integration of visual and range data. To achieve the grand goal, the authors propose an …

We propose a novel and pragmatic framework for traffic scene perception with roadside
cameras. The proposed framework covers a full-stack of roadside perception pipeline for …

Learning contextual and spatial environmental representations enhances autonomous
vehicle's hazard anticipation and decision-making in complex scenarios. Recent perception …

In this work, we tackle two vital tasks in automated driving systems, ie, driver intent prediction
and risk object identification from egocentric images. Mainly, we investigate the question …