KaoKore: A Pre-modern Japanese Art Facial Expression Dataset
KaoKore: A Pre-modern Japanese Art Facial Expression Dataset
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KaoKore：前现代日本艺术面部表情数据集
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
A. Kitamoto
中科院分区：
文献类型：
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作者：
Yingtao Tian;Chikahiko Suzuki;Tarin Clanuwat;Mikel Bober;Alex Lamb;A. Kitamoto
从分类手写数字到生成文本字符串，机器学习社区长期关注的数据集在主题上差异很大。这激发了人们对构建与社会和文化相关的数据集的新兴趣，以便算法研究可以对社会产生更直接和直接的影响。其中一个领域是历史和人文学科，更好且相关的机器学习模型可以加速各个领域的研究。为此，人们提出了新发布的基准和模型来抄写日本历史草书，但对于整个领域来说，使用机器学习来记录日本历史艺术品仍然很大程度上是未知的。为了弥补这一差距，在这项工作中，我们提出了一个新的数据集 KaoKore，它由从前现代日本艺术品中提取的面孔组成。我们展示了它作为图像分类数据集以及创意和艺术数据集的价值，我们使用生成模型对其进行探索。此 https URL 提供数据集
From classifying handwritten digits to generating strings of text, the datasets which have received long-time focus from the machine learning community vary greatly in their subject matter. This has motivated a renewed interest in building datasets which are socially and culturally relevant, so that algorithmic research may have a more direct and immediate impact on society. One such area is in history and the humanities, where better and relevant machine learning models can accelerate research across various fields. To this end, newly released benchmarks and models have been proposed for transcribing historical Japanese cursive writing, yet for the field as a whole using machine learning for historical Japanese artworks still remains largely uncharted. To bridge this gap, in this work we propose a new dataset KaoKore which consists of faces extracted from pre-modern Japanese artwork. We demonstrate its value as both a dataset for image classification as well as a creative and artistic dataset, which we explore using generative models. Dataset available at this https URL