318 citations · 2.1k across the 42 of their papers we have counts for
9 papers · 1 filter
You Only Train Once: Learning a General Anomaly Enhancement Network with Random Masks for Hyperspectral Anomaly Detection
Zhaoxu Li, Yingqian Wang, Chao Xiao +3
In this paper, we introduce a new approach to address the challenge of generalization in hyperspectral anomaly detection (AD). Our method eliminates the need for adjusting paramete…
Disentangling Light Fields for Super-Resolution and Disparity Estimation
Yingqian Wang, Longguang Wang, Gaochang Wu +4
Light field (LF) cameras record both intensity and directions of light rays, and encode 3D scenes into 4D LF images. Recently, many convolutional neural networks (CNNs) have been p…
Local Motion and Contrast Priors Driven Deep Network for Infrared Small Target Super-Resolution
Xinyi Ying, Yingqian Wang, Longguang Wang +4
Infrared small target super-resolution (SR) aims to recover reliable and detailed high-resolution image with high-contrast targets from its low-resolution counterparts. Since the i…
Dense Dual-Attention Network for Light Field Image Super-Resolution
Yu Mo, Yingqian Wang, Chao Xiao +2
Light field (LF) images can be used to improve the performance of image super-resolution (SR) because both angular and spatial information is available. It is challenging to incorp…
A Systematic Survey of Deep Learning-based Single-Image Super-Resolution
Juncheng Li, Zehua Pei, Wenjie Li +4
Single-image super-resolution (SISR) is an important task in image processing, which aims to enhance the resolution of imaging systems. Recently, SISR has made a huge leap and has…
Selective Light Field Refocusing for Camera Arrays Using Bokeh Rendering and Superresolution
Yingqian Wang, Jungang Yang, Yulan Guo +2
Camera arrays provide spatial and angular information within a single snapshot. With refocusing methods, focal planes can be altered after exposure. In this letter, we propose a li…
Light Field Image Super-Resolution Using Deformable Convolution
Yingqian Wang, Jungang Yang, Longguang Wang +4
Light field (LF) cameras can record scenes from multiple perspectives, and thus introduce beneficial angular information for image super-resolution (SR). However, it is challenging…
Spatial-Angular Attention Network for Light Field Reconstruction
Gaochang Wu, Yingqian Wang, Yebin Liu +2
Typical learning-based light field reconstruction methods demand in constructing a large receptive field by deepening the network to capture correspondences between input views. In…
Spatial-Angular Interaction for Light Field Image Super-Resolution
Yingqian Wang, Longguang Wang, Jungang Yang +3
Light field (LF) cameras record both intensity and directions of light rays, and capture scenes from a number of viewpoints. Both information within each perspective (i.e., spatial…