Name
Abstract | ||
|---|---|---|
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... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TMM.2020.3046884 | IEEE Transactions on Multimedia |
Keywords | DocType | Volume |
Image restoration,Anomaly detection,Feature extraction,Semantics,Task analysis,Training,Image reconstruction | Journal | 24 |
ISSN | Citations | PageRank |
1520-9210 | 1 | 0.35 |
References | Authors | |
27 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ye Fei | 1 | 1 | 0.35 |
| Chaoqin Huang | 2 | 1 | 1.02 |
| Jinkun Cao | 3 | 1 | 1.36 |
| Maosen Li | 4 | 34 | 4.15 |
| Ya Zhang | 5 | 1340 | 91.72 |
| Cewu Lu | 6 | 993 | 62.08 |