most citedDual-Hybrid Attention Network for Specular Highlight Removal

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV20242 cited

Dual-Hybrid Attention Network for Specular Highlight Removal

Xiaojiao Guo, Xuhang Chen, Shenghong Luo +2

Specular highlight removal plays a pivotal role in multimedia applications, as it enhances the quality and interpretability of images and videos, ultimately improving the performan…

cs.CV2023

UWFormer: Underwater Image Enhancement via a Semi-Supervised Multi-Scale Transformer

Weiwen Chen, Yingtie Lei, Shenghong Luo +3

Underwater images often exhibit poor quality, distorted color balance and low contrast due to the complex and intricate interplay of light, water, and objects. Despite the signific…

cs.CV2023

ShaDocFormer: A Shadow-Attentive Threshold Detector With Cascaded Fusion Refiner for Document Shadow Removal

Weiwen Chen, Yingtie Lei, Shenghong Luo +3

Document shadow is a common issue that arises when capturing documents using mobile devices, which significantly impacts readability. Current methods encounter various challenges,…

cs.CV2023

Devignet: High-Resolution Vignetting Removal via a Dual Aggregated Fusion Transformer With Adaptive Channel Expansion

Shenghong Luo, Xuhang Chen, Weiwen Chen +3

Vignetting commonly occurs as a degradation in images resulting from factors such as lens design, improper lens hood usage, and limitations in camera sensors. This degradation affe…

cs.CV2023

DocDeshadower: Frequency-Aware Transformer for Document Shadow Removal

Ziyang Zhou, Yingtie Lei, Xuhang Chen +4

Shadows in scanned documents pose significant challenges for document analysis and recognition tasks due to their negative impact on visual quality and readability. Current shadow…