3 citations · 3 across the 7 of their papers we have counts for
9 papers · 1 filter
MedFlowSeg: Flow Matching for Medical Image Segmentation with Frequency-Aware Attention
Zhi Chen, Runze Hu, Le Zhang
Flow matching has recently emerged as a principled framework for learning continuous-time transport maps, enabling efficient ODE-based sampling without relying on stochastic diffus…
DR.Experts: Differential Refinement of Distortion-Aware Experts for Blind Image Quality Assessment
Bohan Fu, Guanyi Qin, Fazhan Zhang +3
Blind Image Quality Assessment, aiming to replicate human perception of visual quality without reference, plays a key role in vision tasks, yet existing models often fail to effect…
BUFF: Bayesian Uncertainty Guided Diffusion Probabilistic Model for Single Image Super-Resolution
Zihao He, Shengchuan Zhang, Runze Hu +2
Super-resolution (SR) techniques are critical for enhancing image quality, particularly in scenarios where high-resolution imagery is essential yet limited by hardware constraints.…
Contrastive Local Manifold Learning for No-Reference Image Quality Assessment
Zihao Huang, Runze Hu, Timin Gao +3
Image Quality Assessment (IQA) methods typically overlook local manifold structures, leading to compromised discriminative capabilities in perceptual quality evaluation. To address…
Multi-Modal Prompt Learning on Blind Image Quality Assessment
Wensheng Pan, Timin Gao, Yan Zhang +10
Image Quality Assessment (IQA) models benefit significantly from semantic information, which allows them to treat different types of objects distinctly. Currently, leveraging seman…
Feature Denoising Diffusion Model for Blind Image Quality Assessment
Xudong Li, Jingyuan Zheng, Runze Hu +8
Blind Image Quality Assessment (BIQA) aims to evaluate image quality in line with human perception, without reference benchmarks. Currently, deep learning BIQA methods typically de…