21 citations · 32 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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…
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…
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…
Mutual Graph Learning for Camouflaged Object Detection
Qiang Zhai, Xin Li, Fan Yang +3
Automatically detecting/segmenting object(s) that blend in with their surroundings is difficult for current models. A major challenge is that the intrinsic similarities between suc…
Cascade Graph Neural Networks for RGB-D Salient Object Detection
Ao Luo, Xin Li, Fan Yang +3
In this paper, we study the problem of salient object detection (SOD) for RGB-D images using both color and depth information.A major technical challenge in performing salient obje…
Hybrid Graph Neural Networks for Crowd Counting
Ao Luo, Fan Yang, Xin Li +4
Crowd counting is an important yet challenging task due to the large scale and density variation. Recent investigations have shown that distilling rich relations among multi-scale…
Reconstructing Perceived Images from Brain Activity by Visually-guided Cognitive Representation and Adversarial Learning
Ziqi Ren, Jie Li, Xuetong Xue +4
Reconstructing visual stimulus (image) only from human brain activity measured with functional Magnetic Resonance Imaging (fMRI) is a significant and meaningful task in Human-AI co…