Abstract RGB-Thermal infrared (RGB-T) image analysis has been actively studied in recent
years. In the past decade, it has received wide attention and made a lot of important …

In the last decade, the computer vision field has seen significant progress in multimodal data
fusion and learning, where multiple sensors, including depth, infrared, and visual, are used …

This paper describes a real-time, high-performance deep-learning network to segment
internal damages of concrete members at the pixel level using active thermography. Unlike …

We propose a novel attention-based framework for 3D human pose estimation from a
monocular video. Despite the general success of end-to-end deep learning paradigms, our …

Visual perception plays an important role in industrial information field, especially in robotic
gras** application. In order to detect the object to be grasped quickly and accurately …

The usage of both off-the-shelf and end-to-end trained deep networks have significantly
improved the performance of visual tracking on RGB videos. However, the lack of large …

The integration of visible and thermal images has demonstrated the potential ability to
enhance crack segmentation accuracy. However, due to the intricate texture of masonry …

Recent deep neural networks based methods have achieved state-of-the-art performance
on various facial expression recognition tasks. Despite such progress, previous researches …

The emergence of large-scale high-quality datasets has stimulated the rapid development of
deep learning in recent years. However, most computer vision tasks focus on the visual …

Despite its promising preliminary results, existing cross-modality Visible-Infrared Person Re-
IDentification (VI-PReID) models incorporating semantic (person) masks simply use these …