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Edit360: 2D Image Edits to 3D Assets From Any Angle

  • Junchao Huang
  • , Xinting Hu
  • , Shaoshuai Shi
  • , Zhuotao Tian
  • , Li Jiang*
  • *Corresponding author for this work
  • The Chinese University of Hong Kong, Shenzhen
  • Nanyang Technological University
  • DiDi Chuxing
  • Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Recent advances in diffusion models have significantly improved image generation and editing, but extending these capabilities to 3D assets remains challenging, especially for fine-grained edits that require multi-view consistency. Existing methods typically restrict editing to predetermined viewing angles, severely limiting their flexibility and practical applications. We introduce Edit360, a tuning-free framework that extends 2D modifications to multi-view consistent 3D editing. Built upon video diffusion models, Edit360 enables user-specific editing from arbitrary view-points while ensuring structural coherence across all views. The framework selects anchor views for 2D modifications and propagates edits across the entire 360 -degree range. To achieve this, Edit360 introduces a novel Anchor-View Editing Propagation mechanism, which effectively aligns and merges multi-view information within the latent and attention spaces of diffusion models. The resulting edited multiview sequences facilitate the reconstruction of high-quality 3D assets, enabling customizable 3D content creation.

Original languageEnglish
Title of host publicationProceedings - 2025 IEEE/CVF International Conference on Computer Vision, ICCV 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages16618-16628
Number of pages11
ISBN (Electronic)9798331587758
DOIs
StatePublished - 2025
Externally publishedYes
Event2025 IEEE/CVF International Conference on Computer Vision, ICCV 2025 - Honolulu, United States
Duration: 19 Oct 202523 Oct 2025

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
ISSN (Print)1550-5499
ISSN (Electronic)2380-7504

Conference

Conference2025 IEEE/CVF International Conference on Computer Vision, ICCV 2025
Country/TerritoryUnited States
CityHonolulu
Period19/10/2523/10/25

Keywords

  • 3d asset generation
  • customizable 3d editing
  • video diffusion models

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