Motion capture technology plays a crucial role in optimizing athletes' skills, techniques, and
strategies by providing detailed feedback on motion data. This article presents a …

Motion deblurring is one of the fundamental problems of computer vision and has received
continuous attention. The variability in blur, both within and across images, imposes …

The study of music-generated dance is a novel and challenging image generation task. It
aims to input a piece of music and seed motions, then generate natural dance movements …

Broad learning system (BLS) is a novel neural network with efficient learning and expansion
capacity, but it is sensitive to noise. Accordingly, the existing robust broad models try to …

Non-autoregressive video captioning methods generate visual words in parallel but often
overlook semantic correlations among them, especially regarding verbs, leading to lower …

Video action recognition aims to classify actions within sequences of video frames, which
has important applications in computer vision fields. Existing methods have shown …

The rise in autonomous vehicles further impacts road networks and driving conditions over
the road networks. Cameras and sensors allow these vehicles to gather the characteristics …

Mainstream RGB-T crowd counting methods use cross-modal complementary information to
improve the counting accuracy. However, most of them neglect the effect of lighting variation …

Face expression recognition in the wild faces challenges such as small data size, low quality
images, and noisy labels. In order to solve these problems, this paper proposes a novel …

In recent years, underwater exploration for deep-sea resource utilization and development
has a considerable interest. In an underwater environment, the obtained images and videos …