Beyond textual constraints : Learning novel diffusion conditions with fewer examples

In this paper, we delve into a novel aspect of learning novel diffusion conditions with datasets an order of magnitude smaller. The rationale behind our approach is the elimination of textual constraints during the few-shot learning process. To that end, we implement two optimization strategies. The...

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Bibliographic Details
Main Authors: YU, Yuyang, LIU, Bangzhen, ZHENG, Chenxi, XU, Xuemiao, ZHANG, Huaidong, HE, Shengfeng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2024
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Online Access:https://ink.library.smu.edu.sg/sis_research/9774
https://ink.library.smu.edu.sg/context/sis_research/article/10774/viewcontent/Yu_Beyond_CVPR_2024_paper.pdf
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Institution: Singapore Management University
Language: English