Interpretable Partitioned Embedding for Customized Multi-item Fashion Outfit Composition-Reference-Cited by-同舟云学术

Interpretable Partitioned Embedding for Customized Multi-item Fashion Outfit Composition

Published:2018-06-05 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval
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Author:

Feng Zunlei¹,Yu Zhenyun¹,Yang Yezhou²,Jing Yongcheng¹,Jiang Junxiao³,Song Mingli¹

Affiliation:

1. Zhejiang University, Hangzhou, China

2. Arizona State University, Phoenix, AZ, USA

3. Alibaba Group, Hangzhou, China

Funder

National Key Research and Development Program

Key Research and Development Program of Zhejiang Province

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3206025.3206048

Reference40 articles.

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2. Apparel Classification with Style

3. Diane Bouchacourt Ryota Tomioka and Sebastian Nowozin. 2017. Multi-level variational autoencoder: Learning disentangled representations from grouped observations. arXiv preprint arX-iv:1705.08841 (2017). Diane Bouchacourt Ryota Tomioka and Sebastian Nowozin. 2017. Multi-level variational autoencoder: Learning disentangled representations from grouped observations. arXiv preprint arX-iv:1705.08841 (2017).

4. Describing Clothing by Semantic Attributes

5. Deep domain adaptation for describing people based on fine-grained clothing attributes

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