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Caricature is an artistic abstraction of the human face by distorting orexaggerating certain facial features, while still retains a likeness with thegiven face. Due to the large diversity of geometric and texture variations,automatic landmark detection and 3D face reconstruction for caricature is achallenging problem and has rarely been studied before. In this paper, wepropose the first automatic method for this task by a novel 3D approach. Tothis end, we first build a dataset with various styles of 2D caricatures andtheir corresponding 3D shapes, and then build a parametric model on vertexbased deformation space for 3D caricature face. Based on the constructeddataset and the nonlinear parametric model, we propose a neural network basedmethod to regress the 3D face shape and orientation from the input 2Dcaricature image. Ablation studies and comparison with state-of-the-art methodsdemonstrate the effectiveness of our algorithm design. Extensive experimentalresults demonstrate that our method works well for various caricatures. Ourconstructed dataset, source code and trained model are available athttps://github.com/Juyong/CaricatureFace.

Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model