33 citations · 45 across the 16 of their papers we have counts for
11 papers · 1 filter
Underwater Image Restoration Through a Prior Guided Hybrid Sense Approach and Extensive Benchmark Analysis
Xiaojiao Guo, Xuhang Chen, Shuqiang Wang +1
Underwater imaging grapples with challenges from light-water interactions, leading to color distortions and reduced clarity. In response to these challenges, we propose a novel Col…
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…
MFDNet: Multi-Frequency Deflare Network for Efficient Nighttime Flare Removal
Yiguo Jiang, Xuhang Chen, Chi-Man Pun +2
When light is scattered or reflected accidentally in the lens, flare artifacts may appear in the captured photos, affecting the photos' visual quality. The main challenge in flare…
MedPrompt: Cross-Modal Prompting for Multi-Task Medical Image Translation
Xuhang Chen, Chi-Man Pun, Shuqiang Wang
Cross-modal medical image translation is an essential task for synthesizing missing modality data for clinical diagnosis. However, current learning-based techniques have limitation…
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…
Generative AI Enables Structural Brain Network Construction from fMRI via Symmetric Diffusion Learning
Qiankun Zuo, Bangjun Lei, Wanyu Qiu +3
Mapping from functional connectivity (FC) to structural connectivity (SC) can facilitate multimodal brain network fusion and discover potential biomarkers for clinical implications…
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,…
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…
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…
A Large-scale Film Style Dataset for Learning Multi-frequency Driven Film Enhancement
Zinuo Li, Xuhang Chen, Shuqiang Wang +1
Film, a classic image style, is culturally significant to the whole photographic industry since it marks the birth of photography. However, film photography is time-consuming and e…
ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal
Xuhang Chen, Xiaodong Cun, Chi-Man Pun +1
Shadow removal improves the visual quality and legibility of digital copies of documents. However, document shadow removal remains an unresolved subject. Traditional techniques rel…