We survey a number of data visualization techniques for analyzing Computer Vision (CV) datasets. These techniques help us understand properties and latent patterns in such data, by applying dataset-level analysis. We present various examples of how such analysis helps predict the potential impact of the dataset properties on CV models and informs appropriate mitigation of their shortcomings. Finally, we explore avenues for further visualization techniques of different modalities of CV datasets as well as ones that are tailored to support specific CV tasks and analysis needs.
翻译：我们调查了用于分析计算机视觉(CV)数据集的若干数据可视化技术,这些技术通过应用数据集级分析,有助于我们了解这些数据中的属性和潜在模式,我们举例说明了这种分析如何有助于预测数据集属性对计算机视觉模型的潜在影响,并为适当减轻其缺陷提供了信息。最后,我们探索了进一步直观化不同模式的计算机视觉数据集技术的途径,以及适合支持特定 CV任务和分析需要的方法。
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