5 papers
DiCLIP: Diffusion Model Enhances CLIP's Dense Knowledge for Weakly Supervised Semantic Segmentation
Zhiwei Yang, Pengfei Song, Yucong Meng +3
Weakly Supervised Semantic Segmentation (WSSS) with image-level labels typically leverages Class Activation Maps (CAMs) to achieve pixel-level predictions. Recently, Contrastive La…
DH-Mamba: Exploring Dual-domain Hierarchical State Space Models for MRI Reconstruction
Yucong Meng, Zhiwei Yang, Zhijian Song +1
The accelerated MRI reconstruction poses a challenging ill-posed inverse problem due to the significant undersampling in k-space. Deep neural networks, such as CNNs and ViTs, have…
Exploring CLIP's Dense Knowledge for Weakly Supervised Semantic Segmentation
Zhiwei Yang, Yucong Meng, Kexue Fu +3
Weakly Supervised Semantic Segmentation (WSSS) with image-level labels aims to achieve pixel-level predictions using Class Activation Maps (CAMs). Recently, Contrastive Language-Im…
MoRe: Class Patch Attention Needs Regularization for Weakly Supervised Semantic Segmentation
Zhiwei Yang, Yucong Meng, Kexue Fu +2
Weakly Supervised Semantic Segmentation (WSSS) with image-level labels typically uses Class Activation Maps (CAM) to achieve dense predictions. Recently, Vision Transformer (ViT) h…
FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image Classification
Kexue Fu, Xiaoyuan Luo, Linhao Qu +5
The expensive fine-grained annotation and data scarcity have become the primary obstacles for the widespread adoption of deep learning-based Whole Slide Images (WSI) classification…