UNPAIRED IMAGE-TO-IMAGE SHAPE TRANSLATION ACROSS FASHION DATA

被引：0

作者：

Wang, Kaili ^{[1
]}

Ma, Liqian ^{[1
]}

Oramas, Jose M. ^{[1
,3
]}

Van Gool, Luc ^{[1
,2
]}

Tuytelaars, Tinne ^{[1
]}

机构：

[1] Katholieke Univ Leuven, ESAT PSI, Leuven, Belgium

[2] ETH D ITET CVL, Zurich, Switzerland

[3] Univ Antwerp, Imec IDLab, Antwerp, Belgium

来源：

2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2020年

关键词：

Image Generation; Image representation;

D O I：

10.1109/icip40778.2020.9190940

中图分类号：

TB8 [摄影技术];

学科分类号：

0804 ;

摘要：

We address the problem of unpaired geometric image-to-image translation. Rather than transferring the style of an image as a whole, our goal is to translate the geometry of an object while preserving its appearance. Our model is trained without the need for paired images. It performs all steps of the shape transfer within a single model and without additional post-processing stages. Experiments on clothing-based datasets show the effectiveness of the proposed method.

引用

页码：206 / 210

页数：5

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