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While 3D GANs have recently demonstrated the high-quality synthesis ofmulti-view consistent images and 3D shapes, they are mainly restricted tophoto-realistic human portraits. This paper aims to extend 3D GANs to adifferent, but meaningful visual form: artistic portrait drawings. However,extending existing 3D GANs to drawings is challenging due to the inevitablegeometric ambiguity present in drawings. To tackle this, we present Dr.3D, anovel adaptation approach that adapts an existing 3D GAN to artistic drawings.Dr.3D is equipped with three novel components to handle the geometricambiguity: a deformation-aware 3D synthesis network, an alternating adaptationof pose estimation and image synthesis, and geometric priors. Experiments showthat our approach can successfully adapt 3D GANs to drawings and enablemulti-view consistent semantic editing of drawings.

Dr.3D: Adapting 3D GANs to Artistic Drawings