Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Sixiao Zheng; Jiachen Lu; Hengshuang Zhao; Xiatian Zhu; Zekun Luo; Yabiao Wang; Yanwei Fu; Jianfeng Feng; Tao Xiang; Philip H. S. Torr; Li Zhang

arXiv · 2012.15840

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Sixiao Zheng·Jiachen Lu·Hengshuang Zhao·Xiatian Zhu·Zekun Luo·Yabiao Wang·Yanwei Fu·Jianfeng Feng·Tao Xiang·Philip H. S. Torr·Li Zhang

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Abstract

Most recent semantic segmentation methods adopt a fully-convolutional network (FCN) with an encoder-decoder architecture. The encoder progressively reduces the spatial resolution and learns more abstract/semantic visual concepts with larger receptive fields. Since context modeling is critical for segmentation, the latest efforts have been focused on increasing the receptive field, through either dilated/atrous convolutions or inserting attention modules. However, the encoder-decoder based FCN architecture remains unchanged. In this paper, we aim to provide an alternative perspective by treating semantic segmentation as a sequence-to-sequence prediction task. Specifically, we deploy a pure transformer (ie, without convolution and resolution reduction) to encode an image as a sequence of patches. With the global context modeled in every layer of the transformer, this encoder can be combined with a simple decoder to provide a powerful segmentation model, termed SEgmentation TRansformer (SETR). Extensive experiments show that SETR achieves new state of the art on ADE20K (50.28% mIoU), Pascal Context (55.83% mIoU) and competitive results on Cityscapes. Particularly, we achieve the first position in the highly competitive ADE20K test server leaderboard on the day of submission.

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BibTeX RIS

Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip H. S. Torr, Li Zhang. 2021-07-25. Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers. https://arxiv.org/abs/2012.15840

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