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title

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raw text

[EMNLP'23] T3H Text-guided 3D Human Generation from 2D Collections Tsu-Jui Fu 1    Wenhan Xiong 2    Yixin Nie 2 Jingyu Liu 2    Barlas Oğuz 2    William Yang Wang 1 1 UC Santa Barbara   2 Meta Conference on Empirical Methods in Natural Language Processing ( EMNLP ) 2023 (Findings) Abstract 3D human modeling has been widely used for engaging interaction in gaming, film, and animation. The customization of these characters is crucial for creativity and scalability, which highlights the importance of controllability. In this work, we introduce Text-guided 3D Human Generation ( T3H ), where a model is to generate a 3D human, guided by the fashion description. There are two goals: 1) the 3D human should render articulately, and 2) its outfit is controlled by the given text. To address this T3H task, we propose Compositional Cross-modal Human (CCH). CCH adopts cross-modal attention to fuse compositional human rendering with the extracted fashion semantics. Ea...

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