6 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…
Continuous K-space Recovery Network with Image Guidance for Fast MRI Reconstruction
Yucong Meng, Zhiwei Yang, Minghong Duan +2
Magnetic resonance imaging (MRI) is a crucial tool for clinical diagnosis while facing the challenge of long scanning time. To reduce the acquisition time, fast MRI reconstruction…
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…
Boosting ViT-based MRI Reconstruction from the Perspectives of Frequency Modulation, Spatial Purification, and Scale Diversification
Yucong Meng, Zhiwei Yang, Yonghong Shi +1
The accelerated MRI reconstruction process presents a challenging ill-posed inverse problem due to the extensive under-sampling in k-space. Recently, Vision Transformers (ViTs) hav…