Barycenters of Natural Images - Constrained Wasserstein Barycenters for Image Morphing
Barycenters of Natural Images - Constrained Wasserstein Barycenters for Image Morphing
复制标题
自然图像的重心 - 用于图像变形的约束 Wasserstein 重心
DOI：
10.1109/cvpr42600.2020.00793
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Aviad Aberdam
中科院分区：
文献类型：
--
作者：
Dror Simon;Aviad Aberdam
图像插值或图像变形是指两个（或多个）输入图像之间的视觉过渡。为了使这种过渡看起来具有视觉吸引力，其理想的特性是：(1)平滑；（ii）对图像进行所需的最小更改；（iii）看起来“真实”，避免在过渡中的每个图像中出现不自然的伪影。为了获得平滑和直接的过渡，可以采用著名的Wasserstein重心问题（WBP）。虽然这种方法保证了在Wasserstein度量下的最小变化，但生成的图像可能看起来不自然。在这项工作中，我们提出了一种具有所有三个所需属性的图像变形新方法。为此，我们定义了WBP的约束变体，强制中间图像满足图像先验。我们描述了一种解决该问题的算法，并使用稀疏先验和生成对抗网络进行了演示。
Image interpolation, or image morphing, refers to a visual transition between two (or more) input images. For such a transition to look visually appealing, its desirable properties are (i) to be smooth; (ii) to apply the minimal required change in the image; and (iii) to seem "real", avoiding unnatural artifacts in each image in the transition. To obtain a smooth and straightforward transition, one may adopt the well-known Wasserstein Barycenter Problem (WBP). While this approach guarantees minimal changes under the Wasserstein metric, the resulting images might seem unnatural. In this work, we propose a novel approach for image morphing that possesses all three desired properties. To this end, we define a constrained variant of the WBP that enforces the intermediate images to satisfy an image prior. We describe an algorithm that solves this problem and demonstrate it using the sparse prior and generative adversarial networks.