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http://hdl.handle.net/10397/89010
Title: | Dual pyramids encoder-decoder network for semantic segmentation in ground and aerial view images | Authors: | Jiang, SL Li, G Yao, W Hong, ZH Kuc, TY |
Issue Date: | 2020 | Source: | International archives of the photogrammetry, remote sensing and spatial information sciences, 2020, v. 43, no. B2, p. 605-610 | Abstract: | Semantic segmentation is a fundamental research task in computer vision, which intends to assign a certain category to every pixel. Currently, most existing methods only utilize the deepest feature map for decoding, while high-level features get inevitably lost during the procedure of down-sampling. In the decoder section, transposed convolution or bilinear interpolation was widely used to restore the size of the encoded feature map; however, few optimizations are applied during up-sampling process which is detrimental to the performance for grouping and classification. In this work, we proposed a dual pyramids encoder-decoder deep neural network (DPEDNet) to tackle the above issues. The first pyramid integrated and encoded multi-resolution features through sequentially stacked merging, and the second pyramid decoded the features through dense atrous convolution with chained up-sampling. Without post-processing and multi-scale testing, the proposed network has achieved state-of-the-art performances on two challenging benchmark image datasets for both ground and aerial view scenes. | Keywords: | Aerial and ground view image Convolution neural network Encoder-Decoder network Semantic segmentation |
Publisher: | Copernicus GmbH | Journal: | International archives of the photogrammetry, remote sensing and spatial information sciences | ISSN: | 1682-1750 | EISSN: | 2194-9034 | DOI: | 10.5194/isprs-archives-XLIII-B2-2020-605-2020 | Description: | 2020 24th ISPRS Congress - Technical Commission II, 31 August - 2 September 2020 | Rights: | © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/). The following publication Jiang, S. L., Li, G., Yao, W., Hong, Z. H., and Kuc, T. Y.: DUAL PYRAMIDS ENCODER-DECODER NETWORK FOR SEMANTIC SEGMENTATION IN GROUND AND AERIAL VIEW IMAGES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 605–610, is available at https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-605-2020, 2020 |
Appears in Collections: | Conference Paper |
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