3 citations · 4 across the 10 of their papers we have counts for
10 papers
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.…
Attention in Diffusion Model: A Survey
Litao Hua, Fan Liu, Jie Su +9
Attention mechanisms have become a foundational component in diffusion models, significantly influencing their capacity across a wide range of generative and discriminative tasks.…
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…
Concealed Object Segmentation with Hierarchical Coherence Modeling
Fengyang Xiao, Pan Zhang, Chunming He +2
Concealed object segmentation (COS) is a challenging task that involves localizing and segmenting those concealed objects that are visually blended with their surrounding environme…
Adaptive Feature Selection for No-Reference Image Quality Assessment by Mitigating Semantic Noise Sensitivity
Xudong Li, Timin Gao, Runze Hu +9
The current state-of-the-art No-Reference Image Quality Assessment (NR-IQA) methods typically rely on feature extraction from upstream semantic backbone networks, assuming that all…
RAUNE-Net: A Residual and Attention-Driven Underwater Image Enhancement Method
Wangzhen Peng, Chenghao Zhou, Runze Hu +2
Underwater image enhancement (UIE) poses challenges due to distinctive properties of the underwater environment, including low contrast, high turbidity, visual blurriness, and colo…