Cross-depiction problem: Recognition and synthesis of photographs and artwork
Cross-depiction problem: Recognition and synthesis of photographs and artwork
复制标题
DOI：
10.1007/s41095-015-0017-1
复制
发表时间：
2015-04
影响因子：
6.9
通讯作者：
P. Hall;Hongping Cai;Qi Wu;Tadeo Corradi
中科院分区：
文献类型：
--
作者：
P. Hall;Hongping Cai;Qi Wu;Tadeo Corradi
交叉描绘是对对象的识别和合成，无论它们是被拍摄、绘制还是绘制等。这是一个重要但研究不足的问题。模仿人类的非凡能力，以令人惊叹的多种描述形式识别和描绘对象，可能会促进计算机视觉的基础和应用。在这篇文章中，我们激发了交叉描述问题，解释了为什么它是困难的，并讨论了一些现有的方法。我们的主要结论是：(I)基于外观的识别系统倾向于过度适应一种描述，(Ii)明确编码部件之间空间关系的模型更稳健，以及(Iii)识别和非照片真实感合成是相关的任务。
Cross-depiction is the recognition—and synthesis—of objects whether they are photographed, painted, drawn, etc. It is a significant yet underresearched problem. Emulating the remarkable human ability to recognise and depict objects in an astonishingly wide variety of depictive forms is likely to advance both the foundations and the applications of computer vision. In this paper we motivate the cross-depiction problem, explain why it is difficult, and discuss some current approaches. Our main conclusions are (i) appearance-based recognition systems tend to be over-fitted to one depiction, (ii) models that explicitly encode spatial relations between parts are more robust, and (iii) recognition and non-photorealistic synthesis are related tasks.