Skip to main content

EASI-Tex: edge-aware mesh texturing from single-image

Resource type
Thesis type
(Thesis) M.Sc.
Date created
We present a novel approach for single-image guided 3D mesh texturing, which employs an image diffusion model with judicious conditioning to transfer textures from a single image to a given 3D shape in a consistent manner. We condition a pre-trained Stable Diffusion generator with edges describing the mesh through ControlNet, and features extracted from the input image using IP-Adapter to produce textures that respect the underlying geometry of the mesh and the input texture without any optimization or training. However, we also introduce Image Inversion, a novel technique to quickly personalize the diffusion model using a single-image, for cases where the pre-trained IP-Adapter falls short in capturing all the details from the input image faithfully. Experimental results showcase the efficiency and effectiveness of our single-image guided edge-aware 3D mesh texturing approach, EASI-Tex, in preserving the details of the input texture on diverse 3D objects while respecting their geometry.
27 pages.
Copyright statement
Copyright is held by the author(s).
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: Zhang, Hao
Member of collection
Download file Size
etd23071.pdf 22.37 MB

Views & downloads - as of June 2023

Views: 0
Downloads: 0