Abstract:
Image became one of the most used form of data we use in our daily life, so as a result image inpainting became one of the most important topics in image processing. Removing an object is very challenging method as it depends on the complexity of the scene, position and the size of the unwanted object. However, deep learning methods have shown great promise in not only providing excellent results in dealing with the most complex scenes, but also the completed region with high quality pixels which makes the whole scene seems to be realistic. This documentation goes through introducing the idea of image inpainting, and discusses the its importance. It explores the used approaches to achieve it, as well as some previous works for such projects and the evaluation of their methods. Moreover, it covers the full implementation details from the very start to the very end of the of the project including the deep learning algorithm we used and the steps of building it. Showing and comparing some results of different models using different evaluation techniques. It also includes the issues we faced during the project and how we solved these problems. Finally, it shows the intended future work for potential modification and improvements for the project