May 24, 2024, 4:50 a.m. | Ganggui Ding, Canyu Zhao, Wen Wang, Zhen Yang, Zide Liu, Hao Chen, Chunhua Shen

cs.CV updates on arXiv.org arxiv.org

arXiv:2405.13870v1 Announce Type: new
Abstract: Benefiting from large-scale pre-trained text-to-image (T2I) generative models, impressive progress has been achieved in customized image generation, which aims to generate user-specified concepts. Existing approaches have extensively focused on single-concept customization and still encounter challenges when it comes to complex scenarios that involve combining multiple concepts. These approaches often require retraining/fine-tuning using a few images, leading to time-consuming training processes and impeding their swift implementation. Furthermore, the reliance on multiple images to represent a singular …

arxiv concept cs.cv free image image generation type

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