Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Novel Recurrent Encoder-Decoder Structure for Large-Scale Multi-view
  Stereo Reconstruction from An Open Aerial Dataset   A great deal of research has demonstrated recently that multi-view stereo
(MVS) matching can be solved with deep learning methods. However, these efforts
were focused on close-range objects and only a very few of the deep
learning-based methods were specifically designed for large-scale 3D urban
reconstruction due to the lack of multi-view aerial image benchmarks. In this
paper, we present a synthetic aerial dataset, called the WHU dataset, we
created for MVS tasks, which, to our knowledge, is the first large-scale
multi-view aerial dataset. It was generated from a highly accurate 3D digital
surface model produced from thousands of real aerial images with precise camera
parameters. We also introduce in this paper a novel network, called RED-Net,
for wide-range depth inference, which we developed from a recurrent
encoder-decoder structure to regularize cost maps across depths and a 2D fully
convolutional network as framework. RED-Net's low memory requirements and high
performance make it suitable for large-scale and highly accurate 3D Earth
surface reconstruction. Our experiments confirmed that not only did our method
exceed the current state-of-the-art MVS methods by more than 50% mean absolute
error (MAE) with less memory and computational cost, but its efficiency as
well. It outperformed one of the best commercial software programs based on
conventional methods, improving their efficiency 16 times over. Moreover, we
proved that our RED-Net model pre-trained on the synthetic WHU dataset can be
efficiently transferred to very different multi-view aerial image datasets
without any fine-tuning. Dataset are available at http://gpcv.whu.edu.cn/data.

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The categories of this paper are: patt-sol
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The categories of this paper are: hep-ex
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The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
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The categories of this paper are: acc-phys
2
The categories of this paper are: math
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The categories of this paper are: econ
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The categories of this paper are: q-fin
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The categories of this paper are: adap-org
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The categories of this paper are: q-bio
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The categories of this paper are: solv-int
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The categories of this paper are: comp-gas
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The categories of this paper are: ao-sci
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The categories of this paper are: atom-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: dg-ga