  In this paper, we propose a novel method for single-view 3D style transfer
that generates a unique 3D object with both shape and texture transfer. Our
focus lies primarily on birds, a popular subject in 3D reconstruction, for
which no existing single-view 3D transfer methods have been developed.The
method we propose seeks to generate a 3D mesh shape and texture of a bird from
two single-view images. To achieve this, we introduce a novel shape transfer
generator that comprises a dual residual gated network (DRGNet), and a
multi-layer perceptron (MLP). DRGNet extracts the features of source and target
images using a shared coordinate gate unit, while the MLP generates spatial
coordinates for building a 3D mesh. We also introduce a semantic UV texture
transfer module that implements textural style transfer using semantic UV
segmentation, which ensures consistency in the semantic meaning of the
transferred regions. This module can be widely adapted to many existing
approaches. Finally, our method constructs a novel 3D bird using a
differentiable renderer. Experimental results on the CUB dataset verify that
our method achieves state-of-the-art performance on the single-view 3D style
transfer task. Code is available in https://github.com/wrk226/creative_birds.
