Search Results for author: Zhikang Li

Found 7 papers, 2 papers with code

Single Stage Virtual Try-on via Deformable Attention Flows

1 code implementation19 Jul 2022 Shuai Bai, Huiling Zhou, Zhikang Li, Chang Zhou, Hongxia Yang

Virtual try-on aims to generate a photo-realistic fitting result given an in-shop garment and a reference person image.

Image Animation Virtual Try-on

M6-Fashion: High-Fidelity Multi-modal Image Generation and Editing

no code implementations24 May 2022 Zhikang Li, Huiling Zhou, Shuai Bai, Peike Li, Chang Zhou, Hongxia Yang

The fashion industry has diverse applications in multi-modal image generation and editing.

Image Generation

Cross-domain User Preference Learning for Cold-start Recommendation

no code implementations7 Dec 2021 Huiling Zhou, Jie Liu, Zhikang Li, Jin Yu, Hongxia Yang

With user history represented by a domain-aware sequential model, a frequency encoder is applied to the underlying tags for user content preference learning.

Recommendation Systems

M6-UFC: Unifying Multi-Modal Controls for Conditional Image Synthesis via Non-Autoregressive Generative Transformers

no code implementations NeurIPS 2021 Zhu Zhang, Jianxin Ma, Chang Zhou, Rui Men, Zhikang Li, Ming Ding, Jie Tang, Jingren Zhou, Hongxia Yang

Conditional image synthesis aims to create an image according to some multi-modal guidance in the forms of textual descriptions, reference images, and image blocks to preserve, as well as their combinations.

Image Generation

UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis

no code implementations NeurIPS 2021 Zhu Zhang, Jianxin Ma, Chang Zhou, Rui Men, Zhikang Li, Ming Ding, Jie Tang, Jingren Zhou, Hongxia Yang

Conditional image synthesis aims to create an image according to some multi-modal guidance in the forms of textual descriptions, reference images, and image blocks to preserve, as well as their combinations.

Image Generation

M6: A Chinese Multimodal Pretrainer

no code implementations1 Mar 2021 Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang

In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1. 9TB images and 292GB texts that cover a wide range of domains.

Image Generation

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