MVPaint: 3D Texture Generation with Multi-View Consistency
texture generation
I have read and agree with the venue's withdrawal policy on behalf of myself and my co-authors.
@misc{
cheng2024mvpaint,
title={{MVP}aint: 3D Texture Generation with Multi-View Consistency},
author={Wei Cheng and Juncheng Mu and Xianfang Zeng and Xin Chen and Anqi Pang and Chi Zhang and Zhibin Wang and Bin Fu and Gang Yu and Ziwei Liu and Liang Pan},
year={2024},
url={https://openreview.net/forum?id=ZGo5VYko2H}
}
Texturing is a crucial step in the 3D asset production workflow, which enhances
the visual appeal and diversity of 3D assets. Despite recent advancements in
generation-based texturing, existing methods often yield subpar results, primar-
ily due to local discontinuities, inconsistencies across multiple views, and their
heavy dependence on UV unwrapping outcomes. To tackle these challenges,
we propose a novel generation-refinement 3D texturing framework called MV-
Paint, which can generate high-resolution, seamless textures while emphasizing
multi-view consistency. Given a 3D mesh model, MVPaint first simultaneously
generates multi-view images by employing a Synchronized Multi-view Genera-
tion (SMG) module, which leads to coarse texturing results with unpainted parts
due to missing observations. To ensure complete 3D texturing, we introduce the
Spatial-aware 3D Inpainting (S3I) method, specifically designed to texture pre-
viously unobserved areas effectively. Furthermore, MVPaint employs a UV Re-
finement (UVR) module for improving the texture quality in the UV space. UVR
first performs a UV-space Super-Resolution, followed by a Spatial-aware Seam-
Smoothing algorithm for revising spatial texturing discontinuities caused by UV
unwrapping. Moreover, we perform meticulous manual annotations to filter the
Objaverse dataset, resulting in around 100,000 high-quality 3D data for texturing
generation. Extensive experimental results demonstrate that MVPaint surpasses
existing state-of-the-art methods. Notably, MVPaint could generate high-fidelity
textures with fewer multi-face issues and better cross-view consistency
I certify that there is no URL (e.g., github page) that could be used to find authors’ identity.
~Wei_Cheng7 ~Juncheng_Mu1 ~Xianfang_Zeng2 ~Xin_Chen16 ~Anqi_Pang1 ~Chi_Zhang13 ~Zhibin_Wang4 ~Bin_Fu3 ~Gang_YU2 ~Ziwei_Liu1 ~Liang_Pan2
Wei Cheng Juncheng Mu Xianfang Zeng Xin Chen Anqi Pang Chi Zhang Zhibin Wang Bin Fu Gang Yu Ziwei Liu Liang Pan
I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics.
texture generation
I certify that there is no acknowledgement section in this submission for double blind review.
cheng|mvpaint_3d_texture_generation_with_multiview_consistency
generative models
I understand the reciprocal reviewing requirement as described on https://iclr.cc/Conferences/2025/CallForPapers. If none of the authors are registered as a reviewer, it may result in a desk rejection at the discretion of the program chairs. To request an exception, please complete this form at https://forms.gle/Huojr6VjkFxiQsUp6.
No
I certify that this submission complies with the submission instructions as described on https://iclr.cc/Conferences/2025/AuthorGuide.
MVPaint: 3D Texture Generation with Multi-View Consistency
ICLR 2025 Conference Withdrawn Submission
ICLR.cc/2025/Conference/Withdrawn_Submission