Transcription of Rethinking Semantic Segmentation From a Sequence-to ...
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Rethinking Semantic Segmentation From a Sequence-to ...
Rethinking Semantic Segmentation from a Sequence-to -Sequence Perspectivewith TransformersSixiao Zheng1*Jiachen Lu1 Hengshuang Zhao2 Xiatian Zhu3 Zekun Luo4 Yabiao Wang4 Yanwei Fu1 Jianfeng Feng1 Tao Xiang3, 5 Philip Torr2Li Zhang1 1 Fudan University2 University of Oxford3 University of Surrey4 Tencent Youtu Lab5 Facebook recent Semantic Segmentation methods adopta fully-convolutional network (FCN) with an encoder-decoder architecture. The encoder progressively reducesthe spatial resolution and learns more abstract/semanticvisual concepts with larger receptive fields. Since contextmodeling is critical for Segmentation , the latest efforts havebeen focused on increasing the receptive field, through ei-ther dilated/atrous convolutions or inserting attention mod-ules. However, the encoder-decoder based FCN architec-ture remains unchanged.
ples the spatial resolution of the input, developing lower-resolution feature mappings useful for discriminating se-mantic classes, and the decoder upsamples the feature rep-
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