1 research outputs found
CaricatureShop: Personalized and Photorealistic Caricature Sketching
In this paper, we propose the first sketching system for interactively
personalized and photorealistic face caricaturing. Input an image of a human
face, the users can create caricature photos by manipulating its facial feature
curves. Our system firstly performs exaggeration on the recovered 3D face model
according to the edited sketches, which is conducted by assigning the laplacian
of each vertex a scaling factor. To construct the mapping between 2D sketches
and a vertex-wise scaling field, a novel deep learning architecture is
developed. With the obtained 3D caricature model, two images are generated, one
obtained by applying 2D warping guided by the underlying 3D mesh deformation
and the other obtained by re-rendering the deformed 3D textured model. These
two images are then seamlessly integrated to produce our final output. Due to
the severely stretching of meshes, the rendered texture is of blurry
appearances. A deep learning approach is exploited to infer the missing details
for enhancing these blurry regions. Moreover, a relighting operation is
invented to further improve the photorealism of the result. Both quantitative
and qualitative experiment results validated the efficiency of our sketching
system and the superiority of our proposed techniques against existing methods.Comment: 12 pages,16 figures,submitted to IEEE TVC