Taming diffusion model for exemplar-based image translation

IF 17.3 3区 计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Hao Ma, Jingyuan Yang, Hui Huang
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引用次数: 0

Abstract

Exemplar-based image translation involves converting semantic masks into photorealistic images that adopt the style of a given exemplar. However, most existing GAN-based translation methods fail to produce photorealistic results. In this study, we propose a new diffusion model-based approach for generating high-quality images that are semantically aligned with the input mask and resemble an exemplar in style. The proposed method trains a conditional denoising diffusion probabilistic model (DDPM) with a SPADE module to integrate the semantic map. We then used a novel contextual loss and auxiliary color loss to guide the optimization process, resulting in images that were visually pleasing and semantically accurate. Experiments demonstrate that our method outperforms state-of-the-art approaches in terms of both visual quality and quantitative metrics.

Abstract Image

驯服基于范例的图像翻译扩散模型
基于范例的图像翻译涉及将语义掩码转换为采用给定范例风格的逼真图像。然而,大多数现有的基于 GAN 的翻译方法都无法生成逼真的结果。在本研究中,我们提出了一种基于扩散模型的新方法,用于生成与输入掩码语义一致、风格类似于范例的高质量图像。该方法利用 SPADE 模块训练条件去噪扩散概率模型 (DDPM),以整合语义图。然后,我们使用新颖的上下文损失和辅助颜色损失来指导优化过程,从而生成视觉上悦目、语义上准确的图像。实验证明,我们的方法在视觉质量和定量指标方面都优于最先进的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computational Visual Media
Computational Visual Media Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
16.90
自引率
5.80%
发文量
243
审稿时长
6 weeks
期刊介绍: Computational Visual Media is a peer-reviewed open access journal. It publishes original high-quality research papers and significant review articles on novel ideas, methods, and systems relevant to visual media. Computational Visual Media publishes articles that focus on, but are not limited to, the following areas: • Editing and composition of visual media • Geometric computing for images and video • Geometry modeling and processing • Machine learning for visual media • Physically based animation • Realistic rendering • Recognition and understanding of visual media • Visual computing for robotics • Visualization and visual analytics Other interdisciplinary research into visual media that combines aspects of computer graphics, computer vision, image and video processing, geometric computing, and machine learning is also within the journal''s scope. This is an open access journal, published quarterly by Tsinghua University Press and Springer. The open access fees (article-processing charges) are fully sponsored by Tsinghua University, China. Authors can publish in the journal without any additional charges.
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