Guided Image-to-Image Translation With Bi-Directional Feature Transformation
Badour Albahar, Jia-Bin Huang
Abstract
Figure 1 . Applications of guided image-to-image translation. We present an algorithm that translates an input image into a corresponding output image while respecting the constraints specified in the provided guidance image. These controllable image-to-image translation problems often require task-specific architectures and training objective functions as the guidance can take various different forms (e.g., color strokes, sketch, texture patch, image, and mask). We introduce a new conditioning scheme for controlling image synthesis using available guidance signals and demonstrate applicability to several sample applications, including person image synthesis guided by a given pose (top), sketch-to-photo synthesis guided with a texture patch (middle), and depth upsampling guided with an RGB image (bottom).
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