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Found 2 papers, 2 papers with code
Anomaly localization by modeling perceptual features
Although unsupervised generative modeling of an image dataset using a Variational AutoEncoder (VAE) has been used to detect anomalous images, or anomalous regions in images, recent works have shown that this method often identifies images or regions that do not concur with human perception, even questioning the usability of generative models for robust anomaly detection.
Ranked #18 on
Anomaly Detection
on VisA
Iterative energy-based projection on a normal data manifold for anomaly localization
Indeed, an autoencoder trained on normal data is expected to only be able to reconstruct normal features of the data, allowing the segmentation of anomalous pixels in an image via a simple comparison between the image and its autoencoder reconstruction.
Ranked #81 on
Anomaly Detection
on MVTec AD
(Segmentation AUROC metric)
