arXiv · 2507.09441
RectifiedHR: High-Resolution Diffusion via Energy Profiling and Adaptive Guidance Scheduling
Abstract
High-resolution image synthesis with diffusion models often suffers from energy instabilities and guidance artifacts that degrade visual quality. We analyze the latent energy landscape during sampling and propose adaptive classifier-free guidance (CFG) schedules that maintain stable energy trajectories. Our approach introduces energy-aware scheduling strategies that modulate guidance strength over time, achieving superior stability scores (0.9998) and consistency metrics (0.9873) compared to fixed-guidance approaches. We demonstrate that DPM++ 2M with linear-decreasing CFG scheduling yields optimal performance, providing sharper, more faithful images while reducing artifacts. Our energy profiling framework serves as a powerful diagnostic tool for understanding and improving diffusion model behavior.
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Ankit Sanjyal. 2025-07-13. RectifiedHR: High-Resolution Diffusion via Energy Profiling and Adaptive Guidance Scheduling. https://arxiv.org/abs/2507.09441
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