23 citations · 35 across the 7 of their papers we have counts for
10 papers
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…
Exploring Sparsity in Image Super-Resolution for Efficient Inference
Longguang Wang, Xiaoyu Dong, Yingqian Wang +4
Current CNN-based super-resolution (SR) methods process all locations equally with computational resources being uniformly assigned in space. However, since missing details in low-…
Learning Local Features with Context Aggregation for Visual Localization
Siyu Hong, Kunhong Li, Yongcong Zhang +3
Keypoint detection and description is fundamental yet important in many vision applications. Most existing methods use detect-then-describe or detect-and-describe strategy to learn…