Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning

1 code implementation • NeurIPS 2021 • Youngkyu Hong, Eunho Yang

In such a biased dataset, models are susceptible to making predictions based on the biased features of the data.

Classification Contrastive Learning

The Majority Can Help The Minority: Context-rich Minority Oversampling for Long-tailed Classification

1 code implementation • CVPR 2022 • Seulki Park, Youngkyu Hong, Byeongho Heo, Sangdoo Yun, Jin Young Choi

The problem of class imbalanced data is that the generalization performance of the classifier deteriorates due to the lack of data from minority classes.

Image Classification Long-tail Learning

Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks

1 code implementation • NeurIPS 2021 • Jinhee Lee, HaeRi Kim, Youngkyu Hong, Hye Won Chung

To promote diversity in sample generation without degrading the overall quality, we propose a simple yet effective method to diagnose and emphasize underrepresented samples during training of a GAN.

Disentangling Label Distribution for Long-tailed Visual Recognition

2 code implementations • CVPR 2021 • Youngkyu Hong, Seungju Han, Kwanghee Choi, Seokjun Seo, Beomsu Kim, Buru Chang

Although this method surpasses state-of-the-art methods on benchmark datasets, it can be further improved by directly disentangling the source label distribution from the model prediction in the training phase.

Image Classification Long-tail Learning