AccDiffusion: An Accurate Method for Higher-Resolution Image Generation
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.
Code (1)
Tasks
Image GenerationObjectMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
AccDiffusion v2: Towards More Accurate Higher-Resolution Diffusion Extrapolation
Diffusion models suffer severe object repetition and local distortion when the inference resolution differs from its pre-trained resolution. We propose AccDiffusion v2, an accurate method for patch-wise higher-resolution…
Image GenerationLocal DistortionScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Models
In this work, we investigate the capability of generating images from pre-trained diffusion models at much higher resolutions than the training image sizes. In addition, the generated images should have arbitrary image a…
Image GenerationMegaFusion: Extend Diffusion Models towards Higher-resolution Image Generation without Further Tuning
Diffusion models have emerged as frontrunners in text-to-image generation, but their fixed image resolution during training often leads to challenges in high-resolution image generation, such as semantic deviations and o…
DenoisingImage GenerationSchedulingText to Image Generation+1CineScale: Tuning-Free High-Resolution Video Generation
Visual diffusion models achieve remarkable progress, yet they are typically trained at limited resolutions due to the lack of high-resolution data and constrained computation resources, hampering their ability to generat…
Video GenerationImage GenerationMake a Cheap Scaling: A Self-Cascade Diffusion Model for Higher-Resolution Adaptation
Diffusion models have proven to be highly effective in image and video generation; however, they still face composition challenges when generating images of varying sizes due to single-scale training data. Adapting large…
Video Generation