Jan 20, 2022 · Abstract page for arXiv paper 2201.08029: Domain Generalization via Frequency-domain-based Feature Disentanglement and Interaction.
Oct 10, 2022 · In this paper, by leveraging the frequency domain of an image, we uniquely work with two key observations: (i) the high-frequency information of ...
Introduction. Code release for "Domain Generalization via Frequency-domain-based Feature Disentanglement and Interaction" (ACM MM 2022): https ...
This paper leverages the image frequency domain to introduce an encoder-decoder structure for high-frequency and low-frequency feature disen-tangling, ...
Sep 6, 2024 · First, the original image is disturbed by FDAG, then the high-and low-frequency features are disentangled by CAE. After that, we interact ...
By leveraging the frequency domain of an image, this paper uniquely work with two key observations: the high-frequency information of animage depicts object ...
Abstract:Data out-of-distribution is a meta-challenge for all statistical learning algorithms that strongly rely on the i.i.d. assumption.
Given the above limitation, this work develops a novel FDA scheme for the DPAD task by exploiting the recapturing distortion models.
Adaptation to out-of-distribution data is a meta-challenge for allstatistical learning algorithms that strongly rely on the i.i.d. ...
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Domain Generalization via Frequency-domain-based Feature Disentanglement and Interaction. Jing-Yi Wang, Ruoyi Du, Dongliang Chang, K. Liang, Zhanyu Ma. 2022 ...