{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/maeday-mae-for-few-and-zero-shot-anomaly","title":"MAEDAY: MAE for few and zero shot AnomalY-Detection","arxiv_id":"2211.14307","date":"2022-11-25","proceeding":null,"authors":["Eli Schwartz","Assaf Arbelle","Leonid Karlinsky","Sivan Harary","Florian Scheidegger","Sivan Doveh","Raja Giryes"],"abstract":"We propose using Masked Auto-Encoder (MAE), a transformer model self-supervisedly trained on image inpainting, for anomaly detection (AD). Assuming anomalous regions are harder to reconstruct compared with normal regions. MAEDAY is the first image-reconstruction-based anomaly detection method that utilizes a pre-trained model, enabling its use for Few-Shot Anomaly Detection (FSAD). We also show the same method works surprisingly well for the novel tasks of Zero-Shot AD (ZSAD) and Zero-Shot Foreign Object Detection (ZSFOD), where no normal samples are available. Code is available at https://github.com/EliSchwartz/MAEDAY .","url_abs":"https://arxiv.org/abs/2211.14307v2","url_pdf":"https://arxiv.org/pdf/2211.14307v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"maeday-mae-for-few-and-zero-shot-anomaly","repo_url":"https://github.com/elischwartz/maeday","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"anomaly-detection","task_name":"Anomaly Detection"},{"task_slug":"image-inpainting","task_name":"Image Inpainting"},{"task_slug":"image-reconstruction","task_name":"Image Reconstruction"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-detection-1","task_name":"object-detection"},{"task_slug":"zero-shot-anomaly-detection","task_name":"zero-shot anomaly detection"}],"methods":[{"method_slug":"mae","method_name":"MAE"},{"method_slug":"fail","method_name":"fail"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2211.14307","atlas_url":"https://app.syntology.ai/?focus=2211.14307","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}