English

Manipulating Vehicle 3D Shapes through Latent Space Editing

Computer Vision and Pattern Recognition 2025-11-17 v1

Abstract

Although 3D object editing has the potential to significantly influence various industries, recent research in 3D generation and editing has primarily focused on converting text and images into 3D models, often overlooking the need for fine-grained control over the editing of existing 3D objects. This paper introduces a framework that employs a pre-trained regressor, enabling continuous, precise, attribute-specific modifications to both the stylistic and geometric attributes of vehicle 3D models. Our method not only preserves the inherent identity of vehicle 3D objects, but also supports multi-attribute editing, allowing for extensive customization without compromising the model's structural integrity. Experimental results demonstrate the efficacy of our approach in achieving detailed edits on various vehicle 3D models.

Keywords

Cite

@article{arxiv.2410.23931,
  title  = {Manipulating Vehicle 3D Shapes through Latent Space Editing},
  author = {JiangDong Miao and Tatsuya Ikeda and Bisser Raytchev and Ryota Mizoguchi and Takenori Hiraoka and Takuji Nakashima and Keigo Shimizu and Toru Higaki and Kazufumi Kaneda},
  journal= {arXiv preprint arXiv:2410.23931},
  year   = {2025}
}

Comments

18 pages, 12 figures

R2 v1 2026-06-28T19:42:53.842Z