Street-view Change Detection via Siamese Encoder-decoder Structured Convolutional Neural Networks

机译：街头视图更改检测通过暹罗编码器 - 解码器结构化卷积神经网络

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In this paper, we propose a siamese encoder-decoder structured network for street scene change detection. The encoder-decoder structures have been successfully applied for semantic segmentation. Our work is inspired by the similarity between change detection and semantic segmentation, and the success of siamese network in comparing image patches. Our method is able to precisely detect changes of street scene at the presence of irrelevant visual differences caused by different shooting conditions and weather. Moreover, the encoder and decoder parts are decoupled. Various combinations of different encoders and decoders are evaluated in this paper. Experiments on two street scene datasets, TSUNAMI and GSV, demonstrate that our method outperforms previous ones by a large margin.

机译：在本文中，我们提出了一种用于街道场景变化检测的暹罗编码器解码器结构化网络。编码器解码器结构已成功应用于语义分割。我们的工作受到改变检测和语义分割之间的相似之处的启发，以及暹罗网络在比较图像斑块时的成功。我们的方法能够在不同拍摄条件和天气引起的无关视觉差异存在下精确地检测街景的变化。此外，编码器和解码器部件分离。本文评估了不同编码器和解码器的各种组合。在两个街道场景数据集，海啸和GSV的实验证明我们的方法通过大幅度优于以前的余量。

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《International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications》|2019年|1(CD-ROM)|共8页
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Xinwei Zhao; Haichang Li; Rui Wang; Changwen Zheng; Song Shi;
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中图分类 TP391.41-53;
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Change detection; Semantic segmentation; Siamese network; Deep learning;

机译：改变检测;语义细分;暹罗网络;深度学习;

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机译：使用暹罗卷积神经网络的光学元件激光诱导的损伤变化检测
2. A Siamese convolutional neural network with high-low level feature fusion for change detection in remotely sensed images [J] . Zhou Hao, Zhang Mi, Hu Xiangyun, Remote sensing letters . 2021,第4a6期

机译：具有高低电平特征融合的暹罗卷积神经网络，用于在远程感测图像中改变检测
3. Change Detection in Multisource VHR Images via Deep Siamese Convolutional Multiple-Layers Recurrent Neural Network [J] . Chen Hongruixuan, Wu Chen, Du Bo, IEEE Transactions on Geoscience and Remote Sensing . 2020,第4期

机译：通过深度暹罗卷积多层反复性神经网络改变多源VHR图像中的检测
4. Street-view Change Detection via Siamese Encoder-decoder Structured Convolutional Neural Networks [C] . Xinwei Zhao, Haichang Li, Rui Wang, International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications . 2019

机译：街头视图更改检测通过暹罗编码器 - 解码器结构化卷积神经网络
5. The Effect of an Additive Loss Function on a Siamese Convolutional Neural Network for Re-Identification Systems [D] . Millar, Matthew Charles. 2020

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6. Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN) [O] . Hu Chen, Yi Zhang, Mannudeep K. Kalra, -1

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7. DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder Convolutional Neural Networks for Pulmonary Nodule Detection [O] . Yuemeng Li, Yang Fan 2020

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Street-view Change Detection via Siamese Encoder-decoder Structured Convolutional Neural Networks

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