3DTextureNet: Neural 3D Texture Style Transfer
Abhinav Upadhyay, Alpana Dubey, Suma Mani Kuriakose · 2023
In our increasingly digital world, there’s a growing demand for 3D models in various fields. Manual 3D model creation is time-consuming and prone to errors, highlighting the need for automation. In this work, we propose a 3D texture transfer framework, 3DTextureNet, to transfer 3D texture from style to content 3D objects, enabling the generation of a wide range of stylized 3D models. We analyze the effects of multiple model hyperparameters on 3D texture transfer. To evaluate the proposed 3D texture transfer framework, we conduct a user study with 3D designers. Our evaluation results demonstrate that our approach effectively transfers 3D texture from style to content objects and the stylized outputs aid in designers’ creativity.