有条件的图像重新绘制
IEEE transactions on pattern analysis and machine intelligence
|November 8, 2023
概括
本研究介绍了条件图像重新绘制 (CIR),这是一个新的图像编辑任务. CIR模型从用户提供的条件中合成现实的视觉效果,增强数字艺术中的创意控制.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 数字图像处理 数字图像处理
背景情况:
- 先进的图像编辑技术擅长根据用户输入生成视觉上有吸引力的结果.
- 现有的方法在根据不同的用户说明合成复杂的视觉内容时提供有限的灵活性.
研究的目的:
- 引入和定义条件图像重新绘制 (CIR) 任务,以合成现实的视觉内容.
- 开发和评估能够处理多种交叉模式条件的新型CIR模型.
- 通过属性和基于语言的颜色规范来增强用户对图像编辑的控制.
主要方法:
- 制定了两阶段CIR模型作为基线方法.
- 设计了统一的CIR模型,其中包含了新的条件聚变模块,以提高性能.
- 利用属性和自然语言输入来指定重新绘制的内容颜色.
- 收集和处理四个不同的数据集来训练和验证模型.
主要成果:
- 在四个数据集中证明了拟议的CIR模型的有效性.
- 在合成基于跨模式条件的现实视觉内容方面取得了显著的改进.
- 通过各种应用场景展示了CIR模型的可用性和实际应用性.
结论:
- 条件图像重新绘制 (CIR) 是图像编辑技术的重大进步.
- 拟议的带有条件融合模块的统一CIR模型提供了更高的性能和灵活性.
- CIR模型为用户提供了一个强大的工具,可以在图像合成中更自由地表达创意意图.
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