Fashion-AttGAN: Attribute-Aware Fashion Editing with Multi-Objective GAN

In this paper, we introduce a novel task, namely attribute-aware fashion-editing, to the fashion domain. A first dataset is constructed for this task with 14,221 images and 22 attributes, which has been made publically available. We re-define the overall objectives in AttGAN and propose the Fashion-AttGAN model to tackle this new task. Experimental results show effectiveness of our Fashion-AttGAN on fashion editing over the original AttGAN.

cs.CV Computer Science

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References (10)

01Generative Adversarial NetworksI. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza et al.2021 · International Conference on Computing Communication and Networking Technologies · 30k citations In Library

02Toward Characteristic-Preserving Image-based Virtual Try-On NetworkBochao Wang, Huabing Zhang, Xiaodan Liang et al.2018 · European Conference on Computer Vision · 496 citations In Library

03Fashion-Gen: The Generative Fashion Dataset and ChallengeNegar Rostamzadeh, Seyedarian Hosseini, Thomas Boquet et al.2018 · arXiv.org · 168 citations In Library

04Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired DataAmjad Almahairi, Sai Rajeswar, Alessandro Sordoni et al.2018 · International Conference on Machine Learning · 465 citations In Library

05AttGAN: Facial Attribute Editing by Only Changing What You WantZhenliang He, W. Zuo, Meina Kan et al.2017 · IEEE Transactions on Image Processing · 830 citations In Library

06Arbitrary Facial Attribute Editing: Only Change What You WantZhenliang He, W. Zuo, Meina Kan et al.2017 · arXiv.org · 57 citations

07VITON: An Image-Based Virtual Try-on NetworkXintong Han, Zuxuan Wu, Zhe Wu et al.2017 · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · 767 citations In Library

08Attribute-Guided Face Generation Using Conditional CycleGANYongyi Lu, Yu-Wing Tai, Chi-Keung Tang2017 · European Conference on Computer Vision · 220 citations

09Invertible Conditional GANs for image editingGuim Perarnau, Joost van de Weijer, B. Raducanu et al.2016 · arXiv.org · 672 citations In Library

10Supplementary materials for: CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training2017 · 338 citations

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