FlexPainter: Flexible and Multi-View Consistent Texture Generation
Authors: name: Dongyu Yan, name: Leyi Wu, name: Jiantao Lin, name: Luozhou Wang, name: Tianshuo Xu, name: Zhifei Chen, name: Zhen Yang, name: Lie Xu, name: Shunsi Zhang, name: Yingcong Chen

Texture map production is an important part of 3D modeling and determines the
rendering quality. Recently, diffusion-based methods have opened a new way for
texture generation. However, restricted control flexibility and limited prompt
modalities may prevent creators from producing desired results. Furthermore,
inconsistencies between generated multi-view images often lead to poor texture
generation quality. To address these issues, we introduce FlexPainter,
a novel texture generation pipeline that enables flexible multi-modal
conditional guidance and achieves highly consistent texture generation. A
shared conditional embedding space is constructed to perform flexible
aggregation between different input modalities. Utilizing such embedding space,
we present an image-based CFG method to decompose structural and style
information, achieving reference image-based stylization. Leveraging the 3D
knowledge within the image diffusion prior, we first generate multi-view images
simultaneously using a grid representation to enhance global understanding.
Meanwhile, we propose a view synchronization and adaptive weighting module
during diffusion sampling to further ensure local consistency. Finally, a
3D-aware texture completion model combined with a texture enhancement model is
used to generate seamless, high-resolution texture maps. Comprehensive
experiments demonstrate that our framework significantly outperforms
state-of-the-art methods in both flexibility and generation quality.