通过关联多分辨率特征投影进行图像染色
IEEE transactions on visualization and computer graphics
|September 13, 2023
概括
本研究介绍了一种新的单阶段多分辨率生成器用于图像绘制,在中等复杂度下获得卓越的结果. 这种新方法有效地合并了本地和全球信息,以改善损坏的图像恢复.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 图像处理 图像处理
背景情况:
- 图像inpainting对于恢复损坏的图像至关重要,现有的方法在质量,复杂性和信息集成之间面临权衡.
- 目前的方法通常使用深度或双阶段网络,导致高计算成本或低于最佳的结果.
- 在平衡油漆质量与效率以及相关的本地-全球信息的方法中存在差距.
研究的目的:
- 提出一种新的单阶段,多分辨率的生成器架构,以实现高效和高质量的图像 inpainting.
- 解决现有方法在复杂性和局部和全球图像特征的整合方面的局限性.
- 为了实现优异的图像重建结果,适度的计算复杂度.
主要方法:
- 开发了一个单阶段的多分辨率生成器架构.
- 引入了多核非本地 (MKNL) 注意区块,用于跨分辨率的功能地图合并.
- 提出了一个特征投射块,用于有效的重建和一个有效的特征融合块,以防止冗余的合并.
主要成果:
- 与最先进的方法相比,拟议的架构展示了优越的图像绘制结果.
- 取得了高质量的结果,复杂度中等,参数数量和运行时间表明.
- 在CelebA-HQ上验证的有效性,卡拉斯等人. 2017,以及使用NVIDIA面具数据集的Places2数据集.
结论:
- 拟议的单阶段多分辨率生成器为绘制图像提供了强大而高效的解决方案.
- 新的注意力和融合块有效地整合了多分辨率功能,以增强图像重建.
- 该方法对移除对象和一般图像恢复等应用具有显著的前景.
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