Papers › AccDiffusion: An Accurate Method for Higher-Resolution Image Generation

AccDiffusion: An Accurate Method for Higher-Resolution Image Generation

15 Jul 2024arXiv:2407.10738archive 2025-07-28

Zhihang Lin, Mingbao Lin, Meng Zhao, Rongrong Ji

This paper attempts to address the object repetition issue in patch-wise higher-resolution image generation. We propose AccDiffusion, an accurate method for patch-wise higher-resolution image generation without training. An in-depth analysis in this paper reveals an identical text prompt for different patches causes repeated object generation, while no prompt compromises the image details. Therefore, our AccDiffusion, for the first time, proposes to decouple the vanilla image-content-aware prompt into a set of patch-content-aware prompts, each of which serves as a more precise description of an image patch. Besides, AccDiffusion also introduces dilated sampling with window interaction for better global consistency in higher-resolution image generation. Experimental comparison with existing methods demonstrates that our AccDiffusion effectively addresses the issue of repeated object generation and leads to better performance in higher-resolution image generation.

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gaussian_filter lzhxmu/AccDiffusion/accdiffusion_sdxl.py official repository ran · our draft was wrong no licence file found · pointer only · d62a181623d1f0cf · report
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rescale_noise_cfg lzhxmu/AccDiffusion/accdiffusion_sdxl.py official repository ran · our draft was wrong fingerprinted no licence file found · pointer only · bea2d776a332f2b0 · report
update_alpha_time_word lzhxmu/AccDiffusion/utils.py official repository ran no licence file found · pointer only · dd498a88e593fe37 · report
create_controller lzhxmu/AccDiffusion/utils.py official repository unverified no licence file found · pointer only · 65c333cf905ea11c · report

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