1.1k citations · 2k across the 34 of their papers we have counts for
60 papers
SDA-Net: Selective Depth Attention Networks for Adaptive Multi-scale Feature Representation
Qingbei Guo, Xiao-Jun Wu, Zhiquan Feng +2
Existing multi-scale solutions lead to a risk of just increasing the receptive field sizes while neglecting small receptive fields. Thus, it is a challenging problem to effectively…
Low-rank features based double transformation matrices learning for image classification
Yu-Hong Cai, Xiao-Jun Wu, Zhe Chen
Linear regression is a supervised method that has been widely used in classification tasks. In order to apply linear regression to classification tasks, a technique for relaxing re…
TGFuse: An Infrared and Visible Image Fusion Approach Based on Transformer and Generative Adversarial Network
Dongyu Rao, Xiao-Jun Wu, Tianyang Xu
The end-to-end image fusion framework has achieved promising performance, with dedicated convolutional networks aggregating the multi-modal local appearance. However, long-range de…
Unsupervised Image Fusion Method based on Feature Mutual Mapping
Dongyu Rao, Xiao-Jun Wu, Tianyang Xu +1
Deep learning-based image fusion approaches have obtained wide attention in recent years, achieving promising performance in terms of visual perception. However, the fusion module…
A Survey for Deep RGBT Tracking
Zhangyong Tang, Tianyang Xu, Xiao-Jun Wu
Visual object tracking with the visible (RGB) and thermal infrared (TIR) electromagnetic waves, shorted in RGBT tracking, recently draws increasing attention in the tracking commun…
Face recognition via compact second order image gradient orientations
He-Feng Yin, Xiao-Jun Wu, Xiaoning Song
Conventional subspace learning approaches based on image gradient orientations only employ the first-order gradient information. However, recent researches on human vision system (…