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cs.CV2024★ 3 cited
DreamDA: Generative Data Augmentation with Diffusion Models
Yunxiang Fu, Chaoqi Chen, Yu Qiao +1
The acquisition of large-scale, high-quality data is a resource-intensive and time-consuming endeavor. Compared to conventional Data Augmentation (DA) techniques (e.g. cropping and…
cs.CV2024
Desigen: A Pipeline for Controllable Design Template Generation
Haohan Weng, Danqing Huang, Yu Qiao +4
Templates serve as a good starting point to implement a design (e.g., banner, slide) but it takes great effort from designers to manually create. In this paper, we present Desigen,…