ImageCaptioner2: Image Captioner for Image Captioning Bias Amplification Assessment
Eslam Abdelrahman,
Pengzhan Sun,
Li Erran Li
et al.
Abstract:Most pre-trained learning systems are known to suffer from bias, which typically emerges from the data, the model, or both. Measuring and quantifying bias and its sources is a challenging task and has been extensively studied in image
captioning. Despite the significant effort in this direction, we observed that existing metrics lack consistency in the inclusion of the visual signal. In this paper, we introduce a new bias assessment metric, dubbed ImageCaptioner2, for image captioning. Instead of measuring the… Show more
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