Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Attribute Restoration Framework for Anomaly Detection   With the recent advances in deep neural networks, anomaly detection in
multimedia has received much attention in the computer vision community. While
reconstruction-based methods have recently shown great promise for anomaly
detection, the information equivalence among input and supervision for
reconstruction tasks can not effectively force the network to learn semantic
feature embeddings. We here propose to break this equivalence by erasing
selected attributes from the original data and reformulate it as a restoration
task, where the normal and the anomalous data are expected to be
distinguishable based on restoration errors. Through forcing the network to
restore the original image, the semantic feature embeddings related to the
erased attributes are learned by the network. During testing phases, because
anomalous data are restored with the attribute learned from the normal data,
the restoration error is expected to be large. Extensive experiments have
demonstrated that the proposed method significantly outperforms several
state-of-the-arts on multiple benchmark datasets, especially on ImageNet,
increasing the AUROC of the top-performing baseline by 10.1%. We also evaluate
our method on a real-world anomaly detection dataset MVTec AD and a video
anomaly detection dataset ShanghaiTech.

14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
3
The categories of this paper are: physics
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
13
The categories of this paper are: quant-ph
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin