✨DyPE: Dynamic Position Extrapolation for Ultra High Resolution Diffusion
📝 Summary:
DyPE enhances diffusion transformers for ultra-high-resolution image generation by dynamically adjusting positional encodings. This training-free method allows pre-trained models to synthesize images far beyond their training resolution, achieving state-of-the-art fidelity without extra sampling ...
🔹 Publication Date: Published on Oct 23
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20766
• PDF: https://arxiv.org/pdf/2510.20766
• Project Page: https://noamissachar.github.io/DyPE/
• Github: https://github.com/guyyariv/DyPE
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#DiffusionModels #ImageGeneration #HighResolution #DeepLearning #ComputerVision
📝 Summary:
DyPE enhances diffusion transformers for ultra-high-resolution image generation by dynamically adjusting positional encodings. This training-free method allows pre-trained models to synthesize images far beyond their training resolution, achieving state-of-the-art fidelity without extra sampling ...
🔹 Publication Date: Published on Oct 23
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20766
• PDF: https://arxiv.org/pdf/2510.20766
• Project Page: https://noamissachar.github.io/DyPE/
• Github: https://github.com/guyyariv/DyPE
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#DiffusionModels #ImageGeneration #HighResolution #DeepLearning #ComputerVision