ODDObjects is designed to detect anomalies of various categories using unsupervised autoencoders trained on COCO-style datasets . Themethod utilizes autoencoder-based image reconstruction, where highreconstruction error indicates the possibility of an anomaly . The frameworkextends previous work on anomaly detection with autoenoders, comparing state-of-the-art models .

Author(s) : Ricky Ma

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Keywords : anomaly - unsupervised - detection - oddobjects - -

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