1.1k citations · 2.2k across the 48 of their papers we have counts for
15 papers · 2 filters
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…
RGBD1K: A Large-scale Dataset and Benchmark for RGB-D Object Tracking
Xue-Feng Zhu, Tianyang Xu, Zhangyong Tang +5
RGB-D object tracking has attracted considerable attention recently, achieving promising performance thanks to the symbiosis between visual and depth channels. However, given a lim…
DreamNet: A Deep Riemannian Network based on SPD Manifold Learning for Visual Classification
Rui Wang, Xiao-Jun Wu, Ziheng Chen +2
Image set-based visual classification methods have achieved remarkable performance, via characterising the image set in terms of a non-singular covariance matrix on a symmetric pos…
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…