Action recognition has already been a heated research topic recently, which attempts to
classify different human actions in videos. The current main-stream methods generally utilize …

Automatic crack detection is challenging due to the poor continuity of cracks, the different
widths of cracks, and the low contrast between cracks and the surrounding pavement. In this …

Rail surface defects are potential danger factors for railway systems, and visual inspection of
surface defects plays a vital role in rail maintenance. Recently, the methods based on deep …

Abstract Cross‐view vehicle Reidentification (ReID) has attracted widespread attention as
an increasingly important vision task in intelligent transportation and urban surveillance …

In this paper, a deep learning method for video‐based action recognition is proposed. On
the one hand, boundary compensation on the basis of a deep neural network is performed …

Automatic synthesis of high quality 3D shapes is an ongoing and challenging area of
research. While several data‐driven methods have been proposed that make use of neural …

Accurate classification of substation equipment images remains challenging due to various
factors such as unexpected illumination, viewing angles, scale variations, shadows, surface …

Generating plausible hair image given limited guidance, such as sparse sketches or low‐
resolution image, has been made possible with the rise of Generative Adversarial Networks …

The semantic representation of deep features is essential for image context understanding,
and effective fusion of features with different semantic representations can significantly …

Purpose Imaging registration has a significant contribution to guide and support physicians
in the process of decision‐making for diagnosis, prognosis, and treatment. However …