2k citations · 6.5k across the 82 of their papers we have counts for
9 papers · 1 filter
Model Inspired Autoencoder for Unsupervised Hyperspectral Image Super-Resolution
Jianjun Liu, Zebin Wu, Liang Xiao +1
This paper focuses on hyperspectral image (HSI) super-resolution that aims to fuse a low-spatial-resolution HSI and a high-spatial-resolution multispectral image to form a high-spa…
Video Is Graph: Structured Graph Module for Video Action Recognition
Rongchang Li, Xiao-Jun Wu, Tianyang Xu
In the field of action recognition, video clips are always treated as ordered frames for subsequent processing. To achieve spatio-temporal perception, existing approaches propose t…
MOON: Multi-Hash Codes Joint Learning for Cross-Media Retrieval
Donglin Zhang, Xiao-Jun Wu, He-Feng Yin +1
In recent years, cross-media hashing technique has attracted increasing attention for its high computation efficiency and low storage cost. However, the existing approaches still h…
UMFA: A photorealistic style transfer method based on U-Net and multi-layer feature aggregation
D. Y. Rao, X. J. Wu, H. Li +2
In this paper, we propose a photorealistic style transfer network to emphasize the natural effect of photorealistic image stylization. In general, distortion of the image content a…
PPT Fusion: Pyramid Patch Transformerfor a Case Study in Image Fusion
Yu Fu, TianYang Xu, XiaoJun Wu +1
The Transformer architecture has witnessed a rapid development in recent years, outperforming the CNN architectures in many computer vision tasks, as exemplified by the Vision Tran…
RFN-Nest: An end-to-end residual fusion network for infrared and visible images
Hui Li, Xiao-Jun Wu, Josef Kittler
In the image fusion field, the design of deep learning-based fusion methods is far from routine. It is invariably fusion-task specific and requires a careful consideration. The mos…
Differentiable Neural Architecture Learning for Efficient Neural Network Design
Qingbei Guo, Xiao-Jun Wu, Josef Kittler +1
Automated neural network design has received ever-increasing attention with the evolution of deep convolutional neural networks (CNNs), especially involving their deployment on emb…
Deep Decomposition Network for Image Processing: A Case Study for Visible and Infrared Image Fusion
Yu Fu, Xiao-Jun Wu, Josef Kittler
Image decomposition is a crucial subject in the field of image processing. It can extract salient features from the source image. We propose a new image decomposition method based…
A Dual-branch Network for Infrared and Visible Image Fusion
Yu Fu, Xiao-Jun Wu
Deep learning is a rapidly developing approach in the field of infrared and visible image fusion. In this context, the use of dense blocks in deep networks significantly improves t…