activity
20242026
most citedA Survey of Camouflaged Object Detection and Beyond

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

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…

cs.CV2025

Uncertainty-Masked Bernoulli Diffusion for Camouflaged Object Detection Refinement

Yuqi Shen, Fengyang Xiao, Sujie Hu +5

Camouflaged Object Detection (COD) presents inherent challenges due to the subtle visual differences between targets and their backgrounds. While existing methods have made notable…

cs.CV2025★ 1 cited

Integrating Extra Modality Helps Segmentor Find Camouflaged Objects Well

Chengyu Fang, Chunming He, Longxiang Tang +6

Camouflaged Object Segmentation (COS) remains challenging because camouflaged objects exhibit only subtle visual differences from their backgrounds and single-modality RGB methods…

cs.CV2024★ 2 cited

A Survey of Camouflaged Object Detection and Beyond

Fengyang Xiao, Sujie Hu, Yuqi Shen +6

Camouflaged Object Detection (COD) refers to the task of identifying and segmenting objects that blend seamlessly into their surroundings, posing a significant challenge for comput…

cs.CV2024★ 1 cited

Diffusion Models in Low-Level Vision: A Survey

Chunming He, Yuqi Shen, Chengyu Fang +6

Deep generative models have garnered significant attention in low-level vision tasks due to their generative capabilities. Among them, diffusion model-based solutions, characterize…