Area of research
Computer Vision and Pattern Recognition · Media Technology
Research interest
Research focused on Artificial intelligence and Image quality, with related work in Contrast (vision), Histogram, Stereoscopy. Notable publications include 'Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data', 'The Analysis of Image Contrast: From Quality Assessment to Automatic Enhancement', and 'No-Reference Quality Metric of Contrast-Distorted Images Based on Information Maximization'.
Single Image Dehazing Using Fuzzy Region Segmentation and Haze Density Decomposition
Unveiling the underwater world: CLIP perception model-guided underwater image enhancement
Blind Quality Assessment of Dense 3D Point Clouds with Structure Guided Resampling
Dynamic Hypergraph Convolutional Network for No-Reference Point Cloud Quality Assessment
CAST: Cross-Modal Retrieval and Visual Conditioning for image captioning
Deep Portrait Quality Assessment. A NTIRE 2024 Challenge Survey
IBVC: Interpolation-driven B-frame video compression
No-Reference Point Cloud Quality Assessment via Graph Convolutional Network
Rethinking and Conceptualizing Just Noticeable Difference Estimation by Residual Learning
Adversarial Exposure Attack on Diabetic Retinopathy Imagery Grading
KSS-ICP: Point Cloud Registration Based on Kendall Shape Space
Real-World Non-Homogeneous Haze Removal by Sliding Self-Attention Wavelet Network
Deep Blind Image Quality Assessment Powered by Online Hard Example Mining
Perception-Driven Similarity-Clarity Tradeoff for Image Super-Resolution Quality Assessment
Single Image Super-Resolution Quality Assessment: A Real-World Dataset, Subjective Studies, and an Objective Metric
CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes
Toward Top-Down Just Noticeable Difference Estimation of Natural Images
Learning Detail-Structure Alternative Optimization for Blind Super-Resolution
Bridging Component Learning With Degradation Modelling for Blind Image Super-Resolution
Progressive Self-Guided Loss for Salient Object Detection
Just Noticeable Difference for Deep Machine Vision
LGGD+: Image Retargeting Quality Assessment by Measuring Local and Global Geometric Distortions
A Dilated Inception Network for Visual Saliency Prediction
Learning a Unified Blind Image Quality Metric via On-Line and Off-Line Big Training Instances
Learning Markov Clustering Networks for Scene Text Detection
Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data
Optimizing Multistage Discriminative Dictionaries for Blind Image Quality Assessment
BLIQUE-TMI: Blind Quality Evaluator for Tone-Mapped Images Based on Local and Global Feature Analyses
QoE-Guided Warping for Stereoscopic Image Retargeting