Eevee - Transforming Images by Bridging High-level Goals and Low-level Edit Operations.

There is a significant gap between the high-level, semantic manner in which we reason about image edits and the low-level, pixel-oriented way in which we execute these edits. While existing image-editing tools provide a great deal of flexibility for professionals, they can be disorienting to novice editors because of the gap between a user's goals and the unfamiliar operations needed to actualize them. We present Eevee, an image-editing system that empowers users to transform images by specifying intents in terms of high-level themes. Based on a provided theme and an understanding of the objects and relationships in the original image, we introduce an optimization function that balances semantic plausibility, visual plausibility, and theme relevance to surface possible image edits. A formative evaluation finds that we are able to guide users to meet their goals while helping them to explore novel, creative ideas for their image edit.