gligen/GLIGEN

Open-Set Grounded Text-to-Image Generation

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GLIGEN: Open-Set Grounded Text-to-Image Generation (CVPR 2023) Yuheng Li, Haotian Liu, Qingyang Wu, Fangzhou Mu, Jianwei Yang, Jianfeng Gao, Chunyuan Li*, Yong Jae Lee* (*Co-senior authors) [Project Page] [Paper] [Demo] [YouTube Video] Go beyond text prompt with GLIGEN: enable new capabilities on frozen text-to-image generation models to ground on various prompts, including box, keypoints and images. GLIGEN’s zero-shot performance on COCO and LVIS outperforms that of existing supervised layout-to-image...
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