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Forsyth, D.A.,
Video Event Detection:
From Subvolume Localization to Spatiotemporal Path Search,
PAMI(36), No. 2, February 2014, pp. 404-416.
IEEE DOI
1402
BibRef
Earlier: A1, A3, Only:
Optimal spatio-temporal path discovery for video event detection,
CVPR11(3321-3328).
IEEE DOI
1106
image motion analysis
BibRef
Yan, X.C.[Xin-Chen],
Yuan, J.S.[Jun-Song],
Liang, H.[Hui],
Efficient Online Spatio-Temporal Filtering for Video Event Detection,
VECTaR14(769-785).
Springer DOI
1504
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Jiang, F.[Fan],
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Anomalous video event detection using spatiotemporal context,
CVIU(115), No. 3, March 2011, pp. 323-333.
Elsevier DOI
1103
BibRef
Earlier:
Video anomaly detection in spatiotemporal context,
ICIP10(705-708).
IEEE DOI
1009
Video surveillance; Anomaly detection; Data mining; Clustering; Context
BibRef
Chang, Y.P.[Yun-Peng],
Tu, Z.G.[Zhi-Gang],
Xie, W.[Wei],
Luo, B.[Bin],
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Yuan, J.S.[Jun-Song],
Video anomaly detection with spatio-temporal dissociation,
PR(122), 2022, pp. 108213.
Elsevier DOI
2112
Video anomaly detection, Spatio-temporal dissociation,
Simulate motion of optical flow, Deep K-means cluster
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Bertini, M.[Marco],
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Multi-scale and real-time non-parametric approach for anomaly detection
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CVIU(116), No. 3, March 2012, pp. 320-329.
Elsevier DOI
1201
BibRef
Earlier: A3, A1, A2:
Dense spatio-temporal features for non-parametric anomaly detection and
localization,
ARTEMIS10(27-32).
DOI Link
1111
Video surveillance; Anomaly detection; Space-time features
BibRef
Liu, K.W.[Kang-Wei],
Wan, J.H.[Jian-Hua],
Han, Z.Z.[Zhong-Zhi],
Abnormal event detection and localization using level set based on
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SIViP(12), No. 2, February 2018, pp. 255-261.
Springer DOI
1802
five image descriptors, namely the color moments, the edge histogram
descriptors, the color and edge directivity descriptors, the color
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BibRef
Ratre, A.[Avinash],
Pankajakshan, V.[Vinod],
Tucker tensor decomposition-based tracking and Gaussian mixture model
for anomaly localisation and detection in surveillance videos,
IET-CV(12), No. 6, September 2018, pp. 933-940.
DOI Link
1808
BibRef
Zhang, X.F.[Xin-Feng],
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Video anomaly detection and localization using motion-field shape
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Elsevier DOI
2006
Abnormal activity, Anomaly detection, Anomaly localization,
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Guo, J.,
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Huang, J.,
Efficient Privacy-Preserving Anomaly Detection and Localization in
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CirSysVideo(30), No. 9, September 2020, pp. 3268-3281.
IEEE DOI
2009
Anomaly detection, Encryption, Cloud computing, Feature extraction,
Servers, Signal processing in the encrypted domain,
cloud computing
BibRef
Lv, H.[Hui],
Zhou, C.W.[Chuan-Wei],
Cui, Z.[Zhen],
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Localizing Anomalies From Weakly-Labeled Videos,
IP(30), 2021, pp. 4505-4515.
IEEE DOI
2105
Videos, Anomaly detection, Location awareness, Semantics, Detectors,
Training, Benchmark testing, Anomaly detection,
traffic anomaly dataset
BibRef
Huang, C.Q.[Chao-Qin],
Xu, Q.[Qinwei],
Wang, Y.F.[Yan-Feng],
Wang, Y.[Yu],
Zhang, Y.[Ya],
Self-Supervised Masking for Unsupervised Anomaly Detection and
Localization,
MultMed(25), 2023, pp. 4426-4438.
IEEE DOI
2310
BibRef
Cao, Y.[Yunkang],
Xu, X.[Xiaohao],
Sun, C.[Chen],
Gao, L.[Liang],
Shen, W.M.[Wei-Ming],
BiaS: Incorporating Biased Knowledge to Boost Unsupervised Image
Anomaly Localization,
SMCS(54), No. 4, April 2024, pp. 2342-2353.
IEEE DOI
2403
Location awareness, Task analysis, Knowledge engineering,
Inspection, Training, Testing, Sun, Anomaly localization, knowledge distillation
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Zhang, H.[Hui],
Wu, Z.[Zuxuan],
Wang, Z.[Zheng],
Chen, Z.[Zhineng],
Jiang, Y.G.[Yu-Gang],
Prototypical Residual Networks for Anomaly Detection and Localization,
CVPR23(16281-16291)
IEEE DOI
2309
BibRef
Singh, A.[Ashish],
Jones, M.J.[Michael J.],
Learned-Miller, E.G.[Erik G.],
EVAL: Explainable Video Anomaly Localization,
CVPR23(18717-18726)
IEEE DOI
2309
BibRef
Liu, Z.K.[Zhi-Kang],
Zhou, Y.M.[Yi-Ming],
Xu, Y.S.[Yuan-Sheng],
Wang, Z.[Zilei],
SimpleNet: A Simple Network for Image Anomaly Detection and
Localization,
CVPR23(20402-20411)
IEEE DOI
2309
BibRef
Heckler, L.[Lars],
König, R.[Rebecca],
Bergmann, P.[Paul],
Exploring the Importance of Pretrained Feature Extractors for
Unsupervised Anomaly Detection and Localization,
VAND23(2917-2926)
IEEE DOI
2309
BibRef
Chiu, L.L.[Li-Ling],
Lai, S.H.[Shang-Hong],
Self-Supervised Normalizing Flows for Image Anomaly Detection and
Localization,
VAND23(2927-2936)
IEEE DOI
2309
BibRef
Panariello, A.[Aniello],
Porrello, A.[Angelo],
Calderara, S.[Simone],
Cucchiara, R.[Rita],
Consistency-based Self-supervised Learning for Temporal Anomaly
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PeopleAn22(338-349).
Springer DOI
2304
BibRef
Schlüter, H.M.[Hannah M.],
Tan, J.[Jeremy],
Hou, B.[Benjamin],
Kainz, B.[Bernhard],
Natural Synthetic Anomalies for Self-supervised Anomaly Detection and
Localization,
ECCV22(XXXI:474-489).
Springer DOI
2211
BibRef
Kawamura, N.[Naoki],
Unsupervised Anomaly Localization Using Locally Adaptive
Query-Dependent Scores,
CIAP22(II:300-311).
Springer DOI
2205
BibRef
Defard, T.[Thomas],
Setkov, A.[Aleksandr],
Loesch, A.[Angelique],
Audigier, R.[Romaric],
Padim: A Patch Distribution Modeling Framework for Anomaly Detection
and Localization,
IML20(475-489).
Springer DOI
2103
BibRef
Venkataramanan, S.[Shashanka],
Peng, K.C.[Kuan-Chuan],
Singh, R.V.[Rajat Vikram],
Mahalanobis, A.[Abhijit],
Attention Guided Anomaly Localization in Images,
ECCV20(XVII:485-503).
Springer DOI
2011
Inspection, surveillance.
BibRef
Pathak, D.[Deepak],
Sharang, A.[Abhijit],
Mukerjee, A.[Amitabha],
Anomaly Localization in Topic-Based Analysis of Surveillance Videos,
WACV15(389-395)
IEEE DOI
1503
Computational modeling
BibRef
Chockalingam, T.[Thiyagarajan],
Emonet, R.[Remi],
Odobez, J.M.[Jean-Marc],
Localized anomaly detection via hierarchical integrated activity
discovery,
AVSS13(51-56)
IEEE DOI
1311
Cameras
BibRef
Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Learning for Detecting Anomalies .