Pedestrians are arguably one of the most safety-critical road users to consider for
autonomous vehicles in urban areas. In this paper, we address the problem of jointly …

Pedestrian detection is central in applications such as autonomous driving. The
performance of algorithms tailored to solve this problem has been extensively evaluated on …

Safe interaction with pedestrians is important for autonomous vehicles in urban
environments. Comprehensive understanding of pedestrian behavior is a challenge for …

Detecting pedestrians with on-board vision systems is of paramount interest for assisting
drivers to prevent vehicle-to-pedestrian accidents. The core of a pedestrian detector is its …

Intelligent transportation systems (ITS) enable transportation participants to communicate
with each other by sending and receiving messages, so that they can be aware of their …

Differential features are popularly used in computer vision tasks, such as object detection. In
this paper, we revisit these features from a functional approximation perspective. In …

Network fusion has been recently explored as an approach for improving pedestrian
detection performance. However, most existing fusion methods suffer from runtime …

Pedestrian detection is the cornerstone of many vision based applications, starting from
object tracking to video surveillance and more recently, autonomous driving. With the rapid …

Data augmentation (DA) is a commonly used method to alleviate the problem of detecting
occluded pedestrians in crowded scenes. Recently, several dataset-level automatic DA …

Pedestrian detection is an initial step to perform outdoor scene analysis, which plays an
essential role in many real-world applications. Although having enjoyed the merits of deep …