arXiv:2407.14982 공식 코드 · Papers with Code

GreenStableYolo: Optimizing Inference Time and Image Quality of Text-to-Image Generation

Jingzhi Gong, Sisi Li, Giordano d'Aloisio, Zishuo Ding, Yulong Ye, William B. Langdon, Federica Sarro

제출 2024-07-20

원문 초록

Tuning the parameters and prompts for improving AI-based text-to-image generation has remained a substantial yet unaddressed challenge. Hence we introduce GreenStableYolo, which improves the parameters and prompts for Stable Diffusion to both reduce GPU inference time and increase image generation quality using NSGA-II and Yolo. Our experiments show that despite a relatively slight trade-off (18%) in image quality compared to StableYolo (which only considers image quality), GreenStableYolo achieves a substantial reduction in inference time (266% less) and a 526% higher hypervolume, thereby advancing the state-of-the-art for text-to-image generation.

함께 살펴볼 논문

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arXiv:2506.23044공통 태그 Image Generation, Text-to-Image Generation, Text to Image Generation공식 코드 · Papers with Code

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