CharGen实现快速精准的角色图像编辑，保持身份一致性。
CharGen: Fast and Fluent Portrait Modification
- 用属性专用滑块控制面部特征、表情等细节
- 速度比现有方法快2-4倍，保留高保真度
- 适合需要高效角色设计的创作者
使用扩散模型进行角色图像交互式编辑仍面临精细控制、生成速度与视觉保真度之间的权衡。我们提出CharGen，一种聚焦角色的编辑器，结合属性特定的Concept Sliders（用于分离并操控面部特征大小、表情、装饰等属性）与StreamDiffusion采样流水线，提升交互性能。为缓解加速采样带来的细节损失，提出轻量级修复步骤，在不破坏结构一致性的前提下恢复细纹理。通过大量消融实验、与开源InstructPix2Pix及闭源Google Gemini对比，以及全面用户研究验证，CharGen在保持身份一致性的同时，实现2至4倍的编辑速度提升。
原文摘要 · Abstract (English)
Interactive editing of character images with diffusion models remains challenging due to the inherent trade-off between fine-grained control, generation speed, and visual fidelity. We introduce CharGen, a character-focused editor that combines attribute-specific Concept Sliders, trained to isolate and manipulate attributes such as facial feature size, expression, and decoration with the StreamDiffusion sampling pipeline for more interactive performance. To counteract the loss of detail that often accompanies accelerated sampling, we propose a lightweight Repair Step that reinstates fine textures without compromising structural consistency. Throughout extensive ablation studies and in comparison to open-source InstructPix2Pix and closed-source Google Gemini, and a comprehensive user study, CharGen achieves two-to-four-fold faster edit turnaround with precise editing control and identity-consistent results. Project page: https://chargen.jdihlmann.com/
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