Dolhasz, A., Harvey, C., Williams, I., 2020.

Towards unsupervised image harmonisation

The field of image synthesis intrinsically relies on the process of image compositing. This process can be automatic or manual, and depends upon artistic intent. Compositing can introduce errors, due to human-detectable differences in the general pixel level transforms of component elements of an image composite. We report on a pilot study evaluating a proof-of-concept automatic image composite harmonisation system consisting of a state-of-the-art deep harmonisation model and a perceptually-based composite luminance artifact detector. We evaluate the performance of both systems on a large data-set of 68128 automatically generated image composites and find that without any task-specific adaptations, the end-to-end system achieves comparable results to the baseline harmoniser fed with ground truth composite masks. We discuss these findings in the context of extending this to an end-to-end, multi-task system.