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cs.CV2026

PRISM: Rethinking Atmospheric Scattering Reconstruction as a Unified Understanding and Restoration Model for Real-world Dehazing

Chengyu Fang, Chunming He, Yuelin Zhang +6

Real-world image dehazing (RID) aims to remove haze-induced degradation from real scenes. This task remains challenging due to non-uniform haze distribution, spatially varying colo…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

Gamma: Toward Generic Image Assessment with Mixture of Assessment Experts

Hantao Zhou, Rui Yang, Longxiang Tang +3

Image assessment aims to evaluate the quality and aesthetics of images and has been applied across various scenarios, such as natural and AIGC scenes. Existing methods mostly addre…

cs.CV2025

UniQA: Unified Vision-Language Pre-training for Image Quality and Aesthetic Assessment

Hantao Zhou, Longxiang Tang, Rui Yang +6

Image Quality Assessment (IQA) and Image Aesthetic Assessment (IAA) aim to simulate human subjective perception of image visual quality and aesthetic appeal. Despite distinct learn…

cs.CV2025

Segment Concealed Objects with Incomplete Supervision

Chunming He, Kai Li, Yachao Zhang +8

Incompletely-Supervised Concealed Object Segmentation (ISCOS) involves segmenting objects that seamlessly blend into their surrounding environments, utilizing incompletely annotate…