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pro vyhledávání: '"Zhai, Zhonghua"'
Autor:
Ju, Chen, Wang, Haicheng, Cheng, Haozhe, Chen, Xu, Zhai, Zhonghua, Huang, Weilin, Lan, Jinsong, Xiao, Shuai, Zheng, Bo
Vision-Language Large Models (VLMs) recently become primary backbone of AI, due to the impressive performance. However, their expensive computation costs, i.e., throughput and delay, impede potentials in the real-world scenarios. To achieve accelerat
Externí odkaz:
http://arxiv.org/abs/2407.11717
Autor:
Xu, Zhengze, Chen, Mengting, Wang, Zhao, Xing, Linyu, Zhai, Zhonghua, Sang, Nong, Lan, Jinsong, Xiao, Shuai, Gao, Changxin
Video try-on is a challenging task and has not been well tackled in previous works. The main obstacle lies in preserving the details of the clothing and modeling the coherent motions simultaneously. Faced with those difficulties, we address video try
Externí odkaz:
http://arxiv.org/abs/2404.17571
In this work, we propose Cell Variational Information Bottleneck Network (cellVIB), a convolutional neural network using information bottleneck mechanism, which can be combined with the latest feedforward network architecture in an end-to-end trainin
Externí odkaz:
http://arxiv.org/abs/2403.15082
This paper introduces a novel framework for virtual try-on, termed Wear-Any-Way. Different from previous methods, Wear-Any-Way is a customizable solution. Besides generating high-fidelity results, our method supports users to precisely manipulate the
Externí odkaz:
http://arxiv.org/abs/2403.12965
Vision-Language Large Models (VLMs) have become primary backbone of AI, due to the impressive performance. However, their expensive computation costs, i.e., throughput and delay, impede potentials in real-world scenarios. To achieve acceleration for
Externí odkaz:
http://arxiv.org/abs/2312.07408
Autor:
Cheng, Zida, Ju, Chen, Xiao, Shuai, Chen, Xu, Zhai, Zhonghua, Zeng, Xiaoyi, Huang, Weilin, Yan, Junchi
The rise of multi-modal search requests from users has highlighted the importance of multi-modal retrieval (i.e. image-to-text or text-to-image retrieval), yet the more complex task of image-to-multi-modal retrieval, crucial for many industry applica
Externí odkaz:
http://arxiv.org/abs/2305.03972
Akademický článek
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Cross-modal retrieval, where the query is an image and the doc is an item with both image and text description, is ubiquitous in e-commerce platforms and content-sharing social media. However, little research attention has been paid to this important
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b43673822b22e93ac48e8edda816a3e
http://arxiv.org/abs/2305.03972
http://arxiv.org/abs/2305.03972
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 2018, Vol. 35 Issue 3, p3043-3049. 7p.
