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

2019/04/16 by Qing Ping, Bing Wu, Ping, Qing +5
Computer Science · Engineering · #3D Shape Modeling and Analysis #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Handwritten Text Recognition Techniques

paper · pdf · doi:10.48550/arxiv.1904.07460

openalex publication_date 2019/04/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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

Citations

• Invertible Conditional GANs for image editing
• Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data
• Fashion-Gen: The Generative Fashion Dataset and Challenge

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• Leveraging Off-the-shelf Diffusion Model for Multi-attribute Fashion Image Manipulation
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