Dataset Groups Activity Stream Random Word Data Augmentation for Zero-Shot Anomaly Detection This paper presents a novel method that leverages a visual-language model, CLIP, as a data source for zero-shot anomaly detection. BibTex: @dataset{Masato_Tamura_2024, abstract = {This paper presents a novel method that leverages a visual-language model, CLIP, as a data source for zero-shot anomaly detection.}, author = {Masato Tamura}, doi = {10.57702/76mdjvra}, institution = {No Organization}, keyword = {'CLIP', 'Random Word Data Augmentation', 'Zero-Shot Anomaly Detection'}, month = {dec}, publisher = {TIB}, title = {Random Word Data Augmentation for Zero-Shot Anomaly Detection}, url = {https://service.tib.eu/ldmservice/dataset/random-word-data-augmentation-for-zero-shot-anomaly-detection}, year = {2024} }
