most citedHigh-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented Transformer

3 citations · 4 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CR2025

Elevating Medical Image Security: A Cryptographic Framework Integrating Hyperchaotic Map and GRU

Weixuan Li, Guang Yu, Quanjun Li +8

Chaotic systems play a key role in modern image encryption due to their sensitivity to initial conditions, ergodicity, and complex dynamics. However, many existing chaos-based encr…

cs.CR2025

TDADL-IE: A Deep Learning-Driven Cryptographic Architecture for Medical Image Security

Junhua Zhou, Quanjun Li, Weixuan Li +7

The rise of digital medical imaging, like MRI and CT, demands strong encryption to protect patient data in telemedicine and cloud storage. Chaotic systems are popular for image enc…

cs.CV2025

CMAMRNet: A Contextual Mask-Aware Network Enhancing Mural Restoration Through Comprehensive Mask Guidance

Yingtie Lei, Fanghai Yi, Yihang Dong +5

Murals, as invaluable cultural artifacts, face continuous deterioration from environmental factors and human activities. Digital restoration of murals faces unique challenges due t…

cs.CV2025

MAC-Lookup: Multi-Axis Conditional Lookup Model for Underwater Image Enhancement

Fanghai Yi, Zehong Zheng, Zexiao Liang +4

Enhancing underwater images is crucial for exploration. These images face visibility and color issues due to light changes, water turbidity, and bubbles. Traditional prior-based me…

eess.IV2025

LensNet: An End-to-End Learning Framework for Empirical Point Spread Function Modeling and Lensless Imaging Reconstruction

Jiesong Bai, Yuhao Yin, Yihang Dong +3

Lensless imaging stands out as a promising alternative to conventional lens-based systems, particularly in scenarios demanding ultracompact form factors and cost-effective architec…

cs.CV2025

DLEN: Dual Branch of Transformer for Low-Light Image Enhancement in Dual Domains

Junyu Xia, Jiesong Bai, Yihang Dong

Low-light image enhancement (LLE) aims to improve the visual quality of images captured in poorly lit conditions, which often suffer from low brightness, low contrast, noise, and c…

cs.CV2024

Underwater Image Restoration via Polymorphic Large Kernel CNNs

Xiaojiao Guo, Yihang Dong, Xuhang Chen +4

Underwater Image Restoration (UIR) remains a challenging task in computer vision due to the complex degradation of images in underwater environments. While recent approaches have l…

cs.CV2024★ 3 cited

High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented Transformer

Mingxian Li, Hao Sun, Yingtie Lei +5

Document images are often degraded by various stains, significantly impacting their readability and hindering downstream applications such as document digitization and analysis. Th…

cs.CV2024

Lagrange Duality and Compound Multi-Attention Transformer for Semi-Supervised Medical Image Segmentation

Fuchen Zheng, Quanjun Li, Weixuan Li +5

Medical image segmentation, a critical application of semantic segmentation in healthcare, has seen significant advancements through specialized computer vision techniques. While d…

cs.CV2024

UIE-UnFold: Deep Unfolding Network with Color Priors and Vision Transformer for Underwater Image Enhancement

Yingtie Lei, Jia Yu, Yihang Dong +3

Underwater image enhancement (UIE) plays a crucial role in various marine applications, but it remains challenging due to the complex underwater environment. Current learning-based…

eess.SP2024★ 1 cited

Multi-modal Mood Reader: Pre-trained Model Empowers Cross-Subject Emotion Recognition

Yihang Dong, Xuhang Chen, Yanyan Shen +3

Emotion recognition based on Electroencephalography (EEG) has gained significant attention and diversified development in fields such as neural signal processing and affective comp…