Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transformations
TransFill-Reference-Inpainting
This is the official repo for TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transformations (Yuqian Zhou, Connelly Barnes, Eli Shechtman, Sohrab Amirghodsi) at CVPR’21. According to some confidential reasons, we are not planning to release the training/testing codes and models. Online-demo will be public once we set up the server. However, we release the testing dataset for comparsion, and the scripts to prepare the training dataset.
Introduction
Image inpainting is the task of plausibly restoring missing pixels within a hole region that is to be removed from a target image. Most existing technologies exploit patch similarities within the image, or leverage large-scale training data to fill the hole using learned semantic and texture information. However, due to the ill-posed nature of the inpainting task,