3 citations · 3 across the 9 of their papers we have counts for
9 papers · 1 filter
RIDE: Retinex-Informed Decoupling for Exposing Concealed Objects
Chunming He, Rihan Zhang, Dingming Zhang +5
Concealed Object Segmentation (COS) encompasses a family of dense-prediction tasks, including camouflaged object detection, polyp segmentation, transparent object detection, and in…
Beyond Ground-Truth: Leveraging Image Quality Priors for Real-World Image Restoration
Fengyang Xiao, Peng Hu, Lei Xu +7
Real-world image restoration aims to restore high-quality (HQ) images from degraded low-quality (LQ) inputs captured under uncontrolled conditions. Existing methods typically depen…
Refining Context-Entangled Content Segmentation via Curriculum Selection and Anti-Curriculum Promotion
Chunming He, Rihan Zhang, Fengyang Xiao +3
Biological learning proceeds from easy to difficult tasks, gradually reinforcing perception and robustness. Inspired by this principle, we address Context-Entangled Content Segment…
Nested Unfolding Network for Real-World Concealed Object Segmentation
Chunming He, Rihan Zhang, Dingming Zhang +3
Deep unfolding networks (DUNs) have recently advanced concealed object segmentation (COS) by modeling segmentation as iterative foreground-background separation. However, existing…
SCALER: SAM-Enhanced Collaborative Learning for Label-Deficient Concealed Object Segmentation
Chunming He, Rihan Zhang, Longxiang Tang +4
Existing methods for label-deficient concealed object segmentation (LDCOS) either rely on consistency constraints or Segment Anything Model (SAM)-based pseudo-labeling. However, th…
UnfoldLDM: Degradation-Aware Unfolding with Iterative Latent Diffusion Priors for Blind Image Restoration
Chunming He, Rihan Zhang, Zheng Chen +6
Deep unfolding networks (DUNs) combine the interpretability of model-based methods with the learning ability of deep networks, yet remain limited for blind image restoration (BIR).…
Reversible Unfolding Network for Concealed Visual Perception with Generative Refinement
Chunming He, Fengyang Xiao, Rihan Zhang +3
Existing methods for concealed visual perception (CVP) often leverage reversible strategies to decrease uncertainty, yet these are typically confined to the mask domain, leaving th…
UnfoldIR: Rethinking Deep Unfolding Network in Illumination Degradation Image Restoration
Chunming He, Rihan Zhang, Fengyang Xiao +4
Deep unfolding networks (DUNs) are widely employed in illumination degradation image restoration (IDIR) to merge the interpretability of model-based approaches with the generalizat…
RUN: Reversible Unfolding Network for Concealed Object Segmentation
Chunming He, Rihan Zhang, Fengyang Xiao +7
Existing concealed object segmentation (COS) methods frequently utilize reversible strategies to address uncertain regions. However, these approaches are typically restricted to th…