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
this https URL

本文提出了一种新方法，用于单视角 3D 风格转换，生成具有形状和纹理转换的独特 3D 对象，主要关注鸟类的 3D 重建，通过引入 DRGNet 和 MLP 构建了一个新型的 3D 鸟类，并使用语义 UV 纹理传输模块实现文本样式转换，最终结果在 CUB 数据集上表现出最先进的性能。