StyleGAN-based CLIP-guided Image Shape Manipulation

被引：0

作者：

Qian, Yuchen ^{[1
]}

Yamamoto, Kohei ^{[1
]}

Yanai, Keiji ^{[1
]}

机构：

[1] Univ Electrocommun, Tokyo, Japan

来源：

19TH INTERNATIONAL CONFERENCE ON CONTENT-BASED MULTIMEDIA INDEXING, CBMI 2022 | 2022年

关键词：

GANs; text-guided image manipulation; image-text cross-modal model; CLIP;

D O I：

10.1145/3549555.3549556

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose a text-guided image manipulation method which focuses on editing shape attribute using text description. We combine an image generation model, StyleGAN2, and image-text matching model, CLIP, and we have achieved the goal of image shape attribute manipulation by modifying the parameters of the pretrained StyleGAN2 generator. Qualitative and quantitative evaluations are conducted to demonstrate the effectiveness of the proposed method.

引用

页码：162 / 166

页数：5

共 29 条

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