Cocktail: mixing multi-modality controls for text-conditional image generation

Cocktail: mixing multi-modality controls for text-conditional image generation

Text-conditional diffusion models are able to generate high-fidelity images with diverse contents. However, linguistic representations frequently exhibit ambiguous descriptions of the envisioned objective imagery, requiring the incorporation of additional control signals to bolster the efficacy of t...

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Bibliographic Details
Main Authors: Hu, Minghui, Zheng, Jianbin, Liu, Daqing, Zheng, Chuanxia, Wang, Chaoyue, Tao, Dacheng, Cham, Tat-Jen
Other Authors: School of Computer Science and Engineering
Format: Conference Paper
Language:English
Published: 2023
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Text-Conditional Image Generation
Computer Graphics
Online Access:https://hdl.handle.net/10356/172668
https://nips.cc/virtual/2023/calendar

Internet

https://hdl.handle.net/10356/172668
https://nips.cc/virtual/2023/calendar

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