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Abstract
The cross-depiction is the recognition -- and synthesis -- of objects whether they are photographed, painted, drawn, etc. It is a significant yet under-researched 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, 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.
In this paper we motivate the cross-depiction problem, explain why it is difficult, 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.
Original language | English |
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Pages (from-to) | 91-103 |
Journal | Computational Visual Media |
Volume | 1 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2015 |
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Dive into the research topics of 'Cross-depiction problem: Recognition and Synthesis of Photographs and Artwork'. Together they form a unique fingerprint.Projects
- 1 Finished
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Classifying Images Regardless of Depictive Style
Hall, P. (PI)
Engineering and Physical Sciences Research Council
24/06/13 → 23/06/16
Project: Research council