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UnitedHuman: Harnessing Multi-Source Data for High-Resolution Human Generation
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UnitedHuman: Harnessing Multi-Source Data for High-Resolution Human Generation UnitedHuman: Harnessing Multi-Source Data for High-Resolution Human Generation ICCV 2023 Jianglin Fu 1* , Shikai Li 1* , Yuming Jiang 2 , Kwan-Yee Lin 1,3 , Wayne Wu 1† , Ziwei Liu 2† 1 Shanghai AI Laboratory, 2 S-Lab, Nanyang Technological University, 3 CUHK Arxiv Video GitHub Abstract Human generation has achieved significant progress. Nonetheless, existing methods still struggle to synthesize specific regions such as faces and hands. We argue that the main reason is rooted in the training data. A holistic human dataset inevitably has insufficient and low-resolution information on local parts. Therefore, we propose to use multi-source datasets with various resolution images to jointly learn a high-resolution human generative model. However, multi-source data inhe...
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