arXiv Computer Vision By Abdul Wasi, Akhil Gorugantu, Mahesh Bhosale, Anjan Dutta, Junsong Yuan, Sauradip Nag, David Doermann

RADI3N: GeometRic ImAge EDiting via ParametrIc 3D CoNtrol

Read the original on arXiv Computer Vision →

RADI3N is a new framework for part‑level image editing that provides parametric 3D control. It introduces a CS‑ARAP deformation module that smooths rotation discontinuities at part boundaries, and an inversion‑free selective texture transfer mechanism that reduces positional bias and enhances semantic matching. The method achieves state‑of‑the‑art results in geometric fidelity, viewpoint consistency, and controllability.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

arXiv Computer Vision
Oct 2

EditVerse3D: High-Quality 3D Object Editing with Region-Aware Learning

arXiv:2607.07187v2 Announce Type: replace Abstract: Local editing of 3D objects remains a long-standing challenge. When interacting with 3D content, humans naturally tend to specify a coarse region o...

By Youtan Yin, Yanning Zhou, Jiacheng Wei, Xiaofeng Yang, Jun Zhang, Jiayang Bai, Jingwen Ye, Weidong Zhang, Guosheng Lin