STEAM: Squeeze and Transform Enhanced Attention Module 事件

STEAM: Squeeze and Transform Enhanced Attention Module arXiv:2412.09023v2 Announce Type: replace Abstract: Channel and spatial attention mechanisms introduced by earlier works enhance the representation abilities of deep convolutional neural networks (CNNs) but often lead to increased parameter and computation costs. While recent approaches focus solely on efficient feature context modeling for channel attention, we aim to model both channel and spatial attention comprehensively with minimal pa