SwinNet: Swin Transformer drives edge-aware RGB-D and RGB-T salient object detection. (arXiv:2204.05585v1 [cs.CV])

Convolutional neural networks (CNNs) are good at extracting contexture
features within certain receptive fields, while transformers can model the
global long-range dependency features. By absorbing the advantage of
transformer and the merit of CNN, Swin Transformer shows strong feature
representation ability. Based on it, we propose a cross-modality fusion model
SwinNet for RGB-D and RGB-T salient object detection. It is driven by Swin
Transformer to extract the hierarchical features, boosted by attention
mechanism to bridge the gap between two modalities, …

arxiv cv detection edge swin transformer