Humans can naturally and effectively find salient regions in complex scenes. Motivated by
this observation, attention mechanisms were introduced into computer vision with the aim of …

Image classification has always been a hot research direction in the world, and the
emergence of deep learning has promoted the development of this field. Convolutional …

Remarkable effectiveness of the channel or spatial attention mechanisms for producing
more discernible feature representation are illustrated in various computer vision tasks …

Recent research on remote sensing object detection has largely focused on improving the
representation of oriented bounding boxes but has overlooked the unique prior knowledge …

Abstract Convolutional Neural Networks (CNNs) have achieved remarkable performance in
various computer vision tasks but this comes at the cost of tremendous computational …

Designing a high-efficiency and high-quality expressive network architecture has always
been the most important research topic in the field of deep learning. Most of today's network …

Road defect detection is a crucial task for promptly repairing road damage and ensuring
road safety. Traditional manual detection methods are inefficient and costly. To overcome …

Abstract Visual Attention Networks (VAN) with Large Kernel Attention (LKA) modules have
been shown to provide remarkable performance, that surpasses Vision Transformers (ViTs) …

Transformer-based method has demonstrated promising performance in image super-
resolution tasks, due to its long-range and global aggregation capability. However, the …

Image dehazing is a representative low-level vision task that estimates latent haze-free
images from hazy images. In recent years, convolutional neural network-based methods …