activity
20212025
most citedShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal

33 citations · 45 across the 16 of their papers we have counts for

collaborators

17 papers

eess.IV2025

UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis

Zhuo Li, Xuhang Chen, Shuqiang Wang +3

Functional ultrasound (fUS) is a neuroimaging technique known for its high spatiotemporal resolution, enabling non-invasive observation of brain activity through neurovascular coup…

cs.CV2025

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…

cs.CV2024★ 2 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.CV2024

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…

cs.CV2023★ 3 cited

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…

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★ 5 cited

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…

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…

q-bio.NC2023

Brain Structure-Function Fusing Representation Learning using Adversarial Decomposed-VAE for Analyzing MCI

Qiankun Zuo, Baiying Lei, Ning Zhong +2

Integrating the brain structural and functional connectivity features is of great significance in both exploring brain science and analyzing cognitive impairment clinically. Howeve…

eess.IV2023

SG-GAN: Fine Stereoscopic-Aware Generation for 3D Brain Point Cloud Up-sampling from a Single Image

Bowen Hu, Weiheng Yao, Sibo Qiao +3

In minimally-invasive brain surgeries with indirect and narrow operating environments, 3D brain reconstruction is crucial. However, as requirements of accuracy for some new minimal…

cs.AI2023

Brain Diffuser: An End-to-End Brain Image to Brain Network Pipeline

Xuhang Chen, Baiying Lei, Chi-Man Pun +1

Brain network analysis is essential for diagnosing and intervention for Alzheimer's disease (AD). However, previous research relied primarily on specific time-consuming and subject…

cs.CV2023

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…

cs.AI2022

Generative artificial intelligence-enabled dynamic detection of nicotine-related circuits

Changwei Gong, Changhong Jing, Ye Li +3

The identification of addiction-related circuits is critical for explaining addiction processes and developing addiction treatments. And models of functional addiction circuits dev…

cs.CV2022★ 33 cited

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…

eess.IV2021★ 2 cited

3D Brain Reconstruction by Hierarchical Shape-Perception Network from a Single Incomplete Image

Bowen Hu, Baiying Lei, Shuqiang Wang +4

3D shape reconstruction is essential in the navigation of minimally-invasive and auto robot-guided surgeries whose operating environments are indirect and narrow, and there have be…