no code implementations • 21 Dec 2023 • Brian Nlong Zhao, Yuhang Xiao, Jiashu Xu, Xinyang Jiang, Yifan Yang, Dongsheng Li, Laurent Itti, Vibhav Vineet, Yunhao Ge
We introduce a solution that allows a pretrained T2I diffusion model to learn a set of soft prompts, enabling the generation of novel images by sampling prompts from the learned distribution.
1 code implementation • 12 Sep 2023 • Yunhao Ge, Jiashu Xu, Brian Nlong Zhao, Neel Joshi, Laurent Itti, Vibhav Vineet
A foreground-background segmentation algorithm is then used to generate foreground object masks.
1 code implementation • 15 Dec 2022 • Yunhao Ge, Jiashu Xu, Brian Nlong Zhao, Laurent Itti, Vibhav Vineet
Finally, the third component creates a large-scale pseudo-labeled instance segmentation training dataset by compositing the foreground object masks onto the original and generated background images.
no code implementations • 20 Jun 2022 • Yunhao Ge, Jiashu Xu, Brian Nlong Zhao, Neel Joshi, Laurent Itti, Vibhav Vineet
For foreground object mask generation, we use a simple textual template with object class name as input to DALL-E to generate a diverse set of foreground images.