Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: FCCDN: Feature Constraint Network for VHR Image Change Detection   Change detection is the process of identifying pixelwise differences in
bitemporal co-registered images. It is of great significance to Earth
observations. Recently, with the emergence of deep learning (DL), the power and
feasibility of deep convolutional neural network (CNN)-based methods have been
shown in the field of change detection. However, there is still a lack of
effective supervision for change feature learning. In this work, a feature
constraint change detection network (FCCDN) is proposed. We constrain features
both in bitemporal feature extraction and feature fusion. More specifically, we
propose a dual encoder-decoder network backbone for the change detection task.
At the center of the backbone, we design a nonlocal feature pyramid network to
extract and fuse multiscale features. To fuse bitemporal features in a robust
way, we build a dense connection-based feature fusion module. Moreover, a
self-supervised learning-based strategy is proposed to constrain feature
learning. Based on FCCDN, we achieve state-of-the-art performance on two
building change detection datasets (LEVIR-CD and WHU). On the LEVIR-CD dataset,
we achieve an IoU of 0.8569 and an F1 score of 0.9229. On the WHU dataset, we
achieve an IoU of 0.8820 and an F1 score of 0.9373. Moreover, for the first
time, the acquisition of accurate bitemporal semantic segmentation results is
achieved without using semantic segmentation labels. This is vital for the
application of change detection because it saves the cost of labeling.

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The categories of this paper are: quant-ph
11
The categories of this paper are: hep-lat
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
29
The categories of this paper are: funct-an
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
0
The categories of this paper are: hep-ph
23
The categories of this paper are: solv-int
16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci