Weakly Supervised High-Fidelity Clothing Model Generation

Author:

Feng Ruili1,Ma Cheng2,Shen Chengji2,Gao Xin3,Liu Zhenjiang3,Li Xiaobo3,Ou Kairi3,Zhao Deli3,Zha Zheng-Jun1

Affiliation:

1. University of Science and Technology of China,Anhui,China

2. Zhejiang University,Hangzhou,China

3. Alibaba Group,Hangzhou,China

Funder

National Key R&D Program of China

National Natural Science Foundation of China (NSFC)

Publisher

IEEE

Reference61 articles.

1. Towards deep learning models resistant to adversarial attacks;madry;ArXiv Preprint,2017

2. VOGUE: Try-on by StyleGAN interpolation optimization;lewis;ArXiv Preprint,2021

3. Analyzing and Improving the Image Quality of StyleGAN

4. A Style-Based Generator Architecture for Generative Adversarial Networks

5. Progressive growing of GANs for improved quality, stability, and variation;karras;Int Conf Learn Represent,0

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2. Cloth2Tex: A Customized Cloth Texture Generation Pipeline for 3D Virtual Try-On;2024 International Conference on 3D Vision (3DV);2024-03-18

3. A Generative Multi-Resolution Pyramid and Normal-Conditioning 3D Cloth Draping;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

4. Taming the Power of Diffusion Models for High-Quality Virtual Try-On with Appearance Flow;Proceedings of the 31st ACM International Conference on Multimedia;2023-10-26

5. Size Does Matter: Size-aware Virtual Try-on via Clothing-oriented Transformation Try-on Network;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

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