AI RESEARCH
SCASeg: Strip Cross-Attention for Efficient Semantic Segmentation
arXiv CS.CV
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ArXi:2411.17061v2 Announce Type: replace The Vision Transformer (ViT) has achieved notable success in computer vision, with its variants widely validated across various downstream tasks, including semantic segmentation. However, as general-purpose visual encoders, ViT backbones often do not fully address the specific requirements of task decoders, highlighting opportunities for designing decoders optimized for efficient semantic segmentation. This paper proposes Strip Cross-Attention (SCASeg), an innovative decoder head specifically designed for semantic segmentation.