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Encoder-DecoderwithAtrous Separable Convolution for ...
Encoder-Decoder with Atrous SeparableConvolution for Semantic Image SegmentationLiang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, andHartwig AdamGoogle Inc.{lcchen, yukun, gpapan, fschroff, pyramid pooling module or encode-decoder structureare used in deep neural networks for semantic segmentation networks are able to encode multi-scale contextual information byprobing the incoming features with filters or pooling operations at mul-tiple rates and multiple effective fields-of-view, while the latter networkscan capture sharper object boundaries by gradually recovering the spatialinformation. In this work, we propose to combine the advantages fromboth methods. Specifically, our proposed model, DeepLabv3+, extendsDeepLabv3 by adding a simple yet effective decoder module to refine thesegmentation results especially along object boundaries.}
Spatial Pyramid Pooling, or ASPP), while PSPNet [24] performs pooling opera-tions at different grid scales. Even though rich semantic information is encoded in the last feature map, detailed information related to object boundaries is missing due to the pooling or convolutions with striding operations within the network backbone.
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