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arXiv (Cornell University)
Noise Diffusion for Enhancing Semantic Faithfulness in Text-to-Image Synthesis
November 2024 • Boming Miao, Chunxiao Li, Xiaoxiao Wang, Andi Zhang, Rui Sun, Zizhe Wang, Yao Zhu
Diffusion models have achieved impressive success in generating photorealistic images, but challenges remain in ensuring precise semantic alignment with input prompts. Optimizing the initial noisy latent offers a more efficient alternative to modifying model architectures or prompt engineering for improving semantic alignment. A latest approach, InitNo, refines the initial noisy latent by leveraging attention maps; however, these maps capture only limited information, and the effectiveness of InitNo is highly depe…
Computer Science
Artificial Intelligence
Computer Vision
Physics