The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
A Revisit of Sparse Coding Based Anomaly Detection in Stacked RNN Framework
Abstract
Motivated by the capability of sparse coding based anomaly detection, we propose a Temporally-coherent Sparse Coding (TSC) where we enforce similar neighbouring frames be encoded with similar reconstruction coefficients. Then we map the TSC with a special type of stacked Recurrent Neural Network (sRNN). By taking advantage of sRNN in learning all parameters simultaneously, the nontrivial hyper-parameter selection to TSC can be avoided, meanwhile with a shallow sRNN, the reconstruction coefficients can be inferred within a forward pass, which reduces the computational cost for learning sparse coefficients. The contributions of this paper are two-fold: i) We propose a TSC, which can be mapped to a sRNN which facilitates the parameter optimization and accelerates the anomaly prediction. ii) We build a very large dataset which is even larger than the summation of all existing dataset for anomaly detection in terms of both the volume of data and the diversity of scenes. Extensive experiments on both a toy dataset and real datasets demonstrate that our TSC based and sRNN based method consistently outperform existing methods, which validates the effectiveness of our method.
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Cites
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Cited by
Gong, D., Liu, L., Le, V., Saha, B., Mansour, M. R., Venkatesh, S., & Van Den Hengel, A. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00179 · Cited by 1,930
Deep Learning for Anomaly Detection: A Survey
Chalapathy, R., & Chawla, S. (2019) · arXiv · doi:10.48550/arxiv.1901.03407 · Cited by 1,240
Gudovskiy, D., Ishizaka, S., & Kozuka, K. (2022) · 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) · doi:10.1109/wacv51458.2022.00188 · Cited by 669
Latent Space Autoregression for Novelty Detection
Abati, D., Porrello, A., Calderara, S., & Cucchiara, R. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00057 · Cited by 508
Sub-Image Anomaly Detection with Deep Pyramid Correspondences
Cohen, N., & Hoshen, Y. (2020) · arXiv · doi:10.48550/arxiv.2005.02357 · Cited by 372
Metadata
- Authors
- Luo, W., Liu, W., & Gao, S.
- Venue
- 2017 IEEE International Conference on Computer Vision (ICCV)
- Publisher
- IEEE
- Published
- 2017-10
- Pages
- 341-349
- OpenAlex
- W2777342313
- Cited by
- 895
- References
- 29
- FWCI
- 16.51
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Luo, W., Liu, W., & Gao, S. (2017). A Revisit of Sparse Coding Based Anomaly Detection in Stacked RNN Framework. 2017 IEEE International Conference on Computer Vision (ICCV). https://doi.org/10.1109/iccv.2017.45
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