Web: http://arxiv.org/abs/2209.08575

Sept. 20, 2022, 1:13 a.m. | Meng-Hao Guo, Cheng-Ze Lu, Qibin Hou, Zhengning Liu, Ming-Ming Cheng, Shi-Min Hu

cs.CV updates on arXiv.org arxiv.org

We present SegNeXt, a simple convolutional network architecture for semantic
segmentation. Recent transformer-based models have dominated the field of
semantic segmentation due to the efficiency of self-attention in encoding
spatial information. In this paper, we show that convolutional attention is a
more efficient and effective way to encode contextual information than the
self-attention mechanism in transformers. By re-examining the characteristics
owned by successful segmentation models, we discover several key components
leading to the performance improvement of segmentation models. This motivates …

arxiv attention design segmentation semantic

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