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Gen4Gen: Generative Data Pipeline for Generative Multi-Concept Composition
Feb. 26, 2024, 5:46 a.m. | Chun-Hsiao Yeh, Ta-Ying Cheng, He-Yen Hsieh, Chuan-En Lin, Yi Ma, Andrew Markham, Niki Trigoni, H. T. Kung, Yubei Chen
cs.CV updates on arXiv.org arxiv.org
Abstract: Recent text-to-image diffusion models are able to learn and synthesize images containing novel, personalized concepts (e.g., their own pets or specific items) with just a few examples for training. This paper tackles two interconnected issues within this realm of personalizing text-to-image diffusion models. First, current personalization techniques fail to reliably extend to multiple concepts -- we hypothesize this to be due to the mismatch between complex scenes and simple text descriptions in the pre-training dataset …
abstract arxiv concept concepts cs.ai cs.cv current data data pipeline diffusion diffusion models examples generative image image diffusion images learn novel paper personalization personalized pets pipeline text text-to-image training type
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