With the rise of deep convolutional neural networks, object detection has achieved
prominent advances in past years. However, such prosperity could not camouflage the …

The past few years have witnessed the immense success of object detection, while current
excellent detectors struggle on tackling size-limited instances. Concretely, the well-known …

This paper explores deep learning (DL) methods that are used or have the potential to be
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …

The challenge of talking face generation from speech lies in aligning two different modal
information, audio and video, such that the mouth region corresponds to input audio …

Black-box unsupervised domain adaptation (UDA) learns with source predictions of target
data without accessing either source data or source models during training, and it has clear …

Radiography imaging protocols focus on particular body regions, therefore producing
images of great similarity and yielding recurrent anatomical structures across patients. To …

Pedestrian detection remains a critical problem in various domains, such as computer
vision, surveillance, and autonomous driving. In particular, accurate and instant detection of …

Visual Speech Recognition (VSR) is a task that recognizes speech from external
appearances of the face (, lips) into text. Since the information from the visual lip movements …

Pedestrian detection is still a challenging task for computer vision, especially in crowded
scenes where the overlaps between pedestrians tend to be large. The non-maximum …

Recently, automated surveillance cameras can change a visible sensor and a thermal
sensor for all-day operation. However, existing single-modal pedestrian detectors mainly …