Deep generative models allow the synthesis of realistic human faces from freehand sketches or semantic maps. However, although they are flexible, sketches and semantic maps provide too much freedom for manipulation, and thus, are not easy for novice users to control. In this study, we present DeepFaceReshaping, a novel landmark-based deep generative framework for interactive face reshaping. To edit the shape of a face realistically by manipulating a small number of face landmarks, we employ neural shape deformation to reshape individual face components. Furthermore, we propose a novel Transformer-based partial refinement network to synthesize the reshaped face components conditioned on the edited landmarks, and fuse the components to generate the entire face using a local-to-global approach. In this manner, we limit possible reshaping effects within a feasible component-based face space. Thus, our interface is intuitive even for novice users, as confirmed by a user study. Our experiments demonstrate that our method outperforms traditional warping-based approaches and recent deep generative techniques.

Image-guided drawing can compensate for a lack of skill but often requires a significant number of repetitive strokes to create textures. Existing automatic stroke synthesis methods are usually limited to predefined styles or require indirect manipulation that may break the spontaneous flow of drawing. We present an assisted drawing system to autocomplete repetitive short strokes during a user’s normal drawing process. Users draw over a reference image as usual; at the same time, our system silently analyzes the input strokes and the reference to infer strokes that follow the user’s input style when certain repetition is detected. Users can accept, modify, or ignore the system’s predictions and continue drawing, thus maintaining fluid control over drawing. Our key idea is to jointly analyze image regions and user input history to detect and predict repetition. The proposed system can effectively reduce the user’s workload when drawing repetitive short strokes, helping users to create results with rich patterns.