Web: http://arxiv.org/abs/2207.10299

Sept. 21, 2022, 1:13 a.m. | Yuhang Zhang, Chengrui Wang, Xu Ling, Weihong Deng

cs.CV updates on arXiv.org arxiv.org

Noisy label Facial Expression Recognition (FER) is more challenging than
traditional noisy label classification tasks due to the inter-class similarity
and the annotation ambiguity. Recent works mainly tackle this problem by
filtering out large-loss samples. In this paper, we explore dealing with noisy
labels from a new feature-learning perspective. We find that FER models
remember noisy samples by focusing on a part of the features that can be
considered related to the noisy labels instead of learning from the whole …

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