Stylistic Multi-Task Analysis of Ukiyo-e Woodblock Prints

Code

• github.com/selinakhan/stylistic-MTL-ukiyoe
  Officialpytorch★ 1

Abstract

In this work we present a large-scale dataset of Ukiyo-e woodblock prints. Unlike previous works and datasets in the artistic domain that primarily focus on western art, this paper explores this pre-modern Japanese art form with the aim of broadening the scope for stylistic analysis and to provide a benchmark to evaluate a variety of art focused Computer Vision approaches. Our dataset consists of over 175.000 prints with corresponding metadata ( artist, era, and creation date) from the 17th century to present day. By approaching stylistic analysis as a Multi-Task problem we aim to more efficiently utilize the available metadata, and learn more general representations of style. We show results for well-known baselines and state-of-the-art multi-task learning frameworks to enable future comparison, and to encourage stylistic analysis on this artistic domain.

Tasks

Reproductions