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5 papers
Cross Paradigm Representation and Alignment Transformer for Image Deraining
Shun Zou, Yi Zou, Juncheng Li +2
Transformer-based networks have achieved strong performance in low-level vision tasks like image deraining by utilizing spatial or channel-wise self-attention. However, irregular r…
Learning Dual-Domain Multi-Scale Representations for Single Image Deraining
Shun Zou, Yi Zou, Mingya Zhang +3
Existing image deraining methods typically rely on single-input, single-output, and single-scale architectures, which overlook the joint multi-scale information between external an…
Fraesormer: Learning Adaptive Sparse Transformer for Efficient Food Recognition
Shun Zou, Yi Zou, Mingya Zhang +3
In recent years, Transformer has witnessed significant progress in food recognition. However, most existing approaches still face two critical challenges in lightweight food recogn…
MambaMIC: An Efficient Baseline for Microscopic Image Classification with State Space Models
Shun Zou, Zhuo Zhang, Yi Zou +1
In recent years, CNN and Transformer-based methods have made significant progress in Microscopic Image Classification (MIC). However, existing approaches still face the dilemma bet…
OCTAMamba: A State-Space Model Approach for Precision OCTA Vasculature Segmentation
Shun Zou, Zhuo Zhang, Guangwei Gao
Optical Coherence Tomography Angiography (OCTA) is a crucial imaging technique for visualizing retinal vasculature and diagnosing eye diseases such as diabetic retinopathy and glau…