2022 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia) 2022
DOI: 10.1109/icce-asia57006.2022.9954841
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Anomaly Segmentation Using Class-aware Erosion and Smoothing

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“…The existing methods for such tasks can be distinguished by whether they use OOD data for training. Some methods expand the training set to include OOD images from other datasets (Hendrycks, Mazeika, and Dietterich 2018a;Chan, Rottmann, and Gottschalk 2021a;Kang, Kwak, and Kang 2022;Tian et al 2022), or utilize large-scale models, e.g., SAM (Kirillov et al 2023) to generate region proposals. Such expansion-based approaches are not of great interest in this paper since we aim to solve the general problem of OOD segmentation without having access to any OOD images for training.…”
Section: Introductionmentioning
confidence: 99%
“…The existing methods for such tasks can be distinguished by whether they use OOD data for training. Some methods expand the training set to include OOD images from other datasets (Hendrycks, Mazeika, and Dietterich 2018a;Chan, Rottmann, and Gottschalk 2021a;Kang, Kwak, and Kang 2022;Tian et al 2022), or utilize large-scale models, e.g., SAM (Kirillov et al 2023) to generate region proposals. Such expansion-based approaches are not of great interest in this paper since we aim to solve the general problem of OOD segmentation without having access to any OOD images for training.…”
Section: Introductionmentioning
confidence: 99%