Icon645

홈페이지 · 논문 1편

Icon645 is a large-scale dataset of icon images that cover a wide range of objects: * 645,687 colored icons * 377 different icon classes These collected icon classes are frequently mentioned in the IconQA questions. In this work, we use the icon data to pre-train backbone networks on the icon classification task in order to extract semantic representations from abstract diagrams in IconQA. On top of pre-training encoders, the large-scale icon data could also contribute to open research on abstract aesthetics and symbolic visual understanding.