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Found 3 papers, 2 papers with code
Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework
Experimental results show the outstanding performance of our proposed approach compared to the state-of-the-art methods, and the proposed RFS energy outperforms the state-of-the-art in the few shot learning settings.
Ranked #63 on
Anomaly Detection
on MVTec AD
Evaluation of Point Pattern Features for Anomaly Detection of Defect within Random Finite Set Framework
The results show that using point pattern features, such as SIFT as data points for random finite set-based anomaly detection achieves the most consistent defect detection accuracy on the MVTec-AD dataset.
Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-Decoding
The proposed approach uses both abnormal and normal video clips during the training phase which is developed in the multiple instance framework where we treat video as a bag and video clips as instances in the bag.
Anomaly Detection In Surveillance Videos
Multiple Instance Learning
+1
