1.0Debiasing vision datasetshttps://mscvprojects.ri.cmu.edu/2025team12-1Background - Debiasing vision datasetsrich600338<blockquote class="wp-embedded-content" data-secret="ShoGrakiTE"><a href="https://mscvprojects.ri.cmu.edu/2025team12-1/background/">Background</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://mscvprojects.ri.cmu.edu/2025team12-1/background/embed/#?secret=ShoGrakiTE" width="600" height="338" title="“Background” — Debiasing vision datasets" data-secret="ShoGrakiTE" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script>
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Existing Approaches Fill-Up: Balancing Long-Tailed Data with Generative Models This paper addresses the challenge of non-uniform data distributions in image classification by leveraging generative models to augment underrepresented classes, thereby balancing the dataset and mitigating bias. The process begins by analyzing the class distribution within the dataset to identify minority classes, which is essential since … Continue reading ""