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CLIP-VQDiffusion : Langauge Free Training of Text To Image generation using CLIP and vector quantized diffusion model
March 25, 2024, 4:44 a.m. | Seungdae Han, Joohee Kim
cs.CV updates on arXiv.org arxiv.org
Abstract: There has been a significant progress in text conditional image generation models. Recent advancements in this field depend not only on improvements in model structures, but also vast quantities of text-image paired datasets. However, creating these kinds of datasets is very costly and requires a substantial amount of labor. Famous face datasets don't have corresponding text captions, making it difficult to develop text conditional image generation models on these datasets. Some research has focused on …
arxiv clip cs.cv diffusion diffusion model free image image generation text training type vector
More from arxiv.org / cs.CV updates on arXiv.org
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs
2 days, 6 hours ago |
arxiv.org
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