Feb. 14, 2024, 5:46 a.m. | AprilPyone MaungMaung Huy H. Nguyen Hitoshi Kiya Isao Echizen

cs.CV updates on arXiv.org arxiv.org

We propose a method for generating spurious features by leveraging large-scale text-to-image diffusion models. Although the previous work detects spurious features in a large-scale dataset like ImageNet and introduces Spurious ImageNet, we found that not all spurious images are spurious across different classifiers. Although spurious images help measure the reliance of a classifier, filtering many images from the Internet to find more spurious features is time-consuming. To this end, we utilize an existing approach of personalizing large-scale text-to-image diffusion models …

class classifiers cs.cv dataset diffusion diffusion models feature features fine-tuning found image image diffusion imagenet images reliance scale text text-to-image wise work

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