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Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark.

, , , , , , , and . CoRR, (2024)

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Beyond Triplet Loss: Person Re-Identification With Fine-Grained Difference-Aware Pairwise Loss., , , , , , and . IEEE Trans. Multim., (2022)LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Anomaly Detection., , , , , , and . CoRR, (2023)Feature Prediction Diffusion Model for Video Anomaly Detection., , , , and . ICCV, page 5504-5514. IEEE, (2023)Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data., , , and . KDD, page 1298-1308. ACM, (2021)ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation., , , , and . KDD, page 4892-4893. ACM, (2022)VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection., , , , , , and . AAAI, page 6074-6082. AAAI Press, (2024)LeSiNN: Detecting Anomalies by Identifying Least Similar Nearest Neighbours., , and . ICDM Workshops, page 623-630. IEEE Computer Society, (2015)Graph-level Anomaly Detection via Hierarchical Memory Networks., , and . CoRR, (2023)OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning., , , , , and . CoRR, (2024)AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection., , , , and . ICLR, OpenReview.net, (2024)