技术背景与现状

• 动漫角色生成的技术分类（GAN、Diffusion Models等）
• 当前主流工具与框架（Stable Diffusion、NovelAI等）
• 行业应用案例（游戏、影视、插画设计）

比赛核心技术与难点

• 角色一致性保持（多角度、多姿态生成）
• 细节控制（服饰、发型、色彩风格）
• 数据需求与版权问题（训练集构建）

参赛方案设计要点

• 模型选型与微调策略（LoRA、ControlNet等轻量级适配）
• 提示词工程（Tag组合、权重分配）
• 后处理优化（超分辨率、缺陷修复）

评价标准与优化方向

• 主观指标（美观度、创意性）
• 客观指标（生成速度、资源消耗）
• 常见问题解决方案（面部畸变、肢体错误）
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未来发展趋势

• 3D角色生成与动态化
• 用户交互式设计工具
• 开源生态与社区贡献