March 28, 2024, 4:45 a.m. | Jianshu Guo, Wenhao Chai, Jie Deng, Hsiang-Wei Huang, Tian Ye, Yichen Xu, Jiawei Zhang, Jenq-Neng Hwang, Gaoang Wang

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.18493v1 Announce Type: new
Abstract: Recent text-to-image (T2I) models have benefited from large-scale and high-quality data, demonstrating impressive performance. However, these T2I models still struggle to produce images that are aesthetically pleasing, geometrically accurate, faithful to text, and of good low-level quality. We present VersaT2I, a versatile training framework that can boost the performance with multiple rewards of any T2I model. We decompose the quality of the image into several aspects such as aesthetics, text-image alignment, geometry, low-level quality, etc. …

abstract arxiv boost cs.cv data framework good however image images improving low performance quality quality data scale struggle text text-to-image training type

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