23 citations · 54 across the 10 of their papers we have counts for
15 papers
NTIRE 2024 Challenge on Stereo Image Super-Resolution: Methods and Results
Longguang Wang, Yulan Guo, Juncheng Li +6
This paper summarizes the 3rd NTIRE challenge on stereo image super-resolution (SR) with a focus on new solutions and results. The task of this challenge is to super-resolve a low-…
NTIRE 2022 Challenge on Stereo Image Super-Resolution: Methods and Results
Longguang Wang, Yulan Guo, Yingqian Wang +3
In this paper, we summarize the 1st NTIRE challenge on stereo image super-resolution (restoration of rich details in a pair of low-resolution stereo images) with a focus on new sol…
Occlusion-Aware Cost Constructor for Light Field Depth Estimation
Yingqian Wang, Longguang Wang, Zhengyu Liang +3
Matching cost construction is a key step in light field (LF) depth estimation, but was rarely studied in the deep learning era. Recent deep learning-based LF depth estimation metho…
Unsupervised Degradation Representation Learning for Blind Super-Resolution
Longguang Wang, Yingqian Wang, Xiaoyu Dong +4
Most existing CNN-based super-resolution (SR) methods are developed based on an assumption that the degradation is fixed and known (e.g., bicubic downsampling). However, these meth…
Symmetric Parallax Attention for Stereo Image Super-Resolution
Yingqian Wang, Xinyi Ying, Longguang Wang +3
Although recent years have witnessed the great advances in stereo image super-resolution (SR), the beneficial information provided by binocular systems has not been fully used. Sin…
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…