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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Main Authors: | , , , , , , |
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Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/172668 https://nips.cc/virtual/2023/calendar |
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Institution: | Nanyang Technological University |
Language: | English |
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