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20192025
most citedMutual Graph Learning for Camouflaged Object Detection

21 citations · 27 across the 9 of their papers we have counts for

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Showing cs.CVShow all

10 papers · 1 filter

cs.CV2025

MExD: An Expert-Infused Diffusion Model for Whole-Slide Image Classification

Jianwei Zhao, Xin Li, Fan Yang +5

Whole Slide Image (WSI) classification poses unique challenges due to the vast image size and numerous non-informative regions, which introduce noise and cause data imbalance durin…

cs.CV20242 cited

FocusDiffuser: Perceiving Local Disparities for Camouflaged Object Detection

Jianwei Zhao, Xin Li, Fan Yang +4

Detecting objects seamlessly blended into their surroundings represents a complex task for both human cognitive capabilities and advanced artificial intelligence algorithms. Curren…

cs.CV2023

GAFlow: Incorporating Gaussian Attention into Optical Flow

Ao Luo, Fan Yang, Xin Li +4

Optical flow, or the estimation of motion fields from image sequences, is one of the fundamental problems in computer vision. Unlike most pixel-wise tasks that aim at achieving con…

cs.CV20232 cited

Cross-supervised Dual Classifiers for Semi-supervised Medical Image Segmentation

Zhenxi Zhang, Ran Ran, Chunna Tian +4

Semi-supervised medical image segmentation offers a promising solution for large-scale medical image analysis by significantly reducing the annotation burden while achieving compar…

cs.CV20231 cited

Self-aware and Cross-sample Prototypical Learning for Semi-supervised Medical Image Segmentation

Zhenxi Zhang, Ran Ran, Chunna Tian +4

Consistency learning plays a crucial role in semi-supervised medical image segmentation as it enables the effective utilization of limited annotated data while leveraging the abund…

cs.CV20221 cited

Learning Optical Flow with Adaptive Graph Reasoning

Ao Luo, Fan Yang, Kunming Luo +3

Estimating per-pixel motion between video frames, known as optical flow, is a long-standing problem in video understanding and analysis. Most contemporary optical flow techniques l…