Kavli Affiliate: Xiang Zhang
| First 5 Authors: Zeng Tao, Zeng Tao, , ,
| Summary:
Existing 2D-lifting-based 3D editing methods often encounter challenges
related to inconsistency, stemming from the lack of view-consistent 2D editing
models and the difficulty of ensuring consistent editing across multiple views.
To address these issues, we propose C3Editor, a controllable and consistent
2D-lifting-based 3D editing framework. Given an original 3D representation and
a text-based editing prompt, our method selectively establishes a
view-consistent 2D editing model to achieve superior 3D editing results. The
process begins with the controlled selection of a ground truth (GT) view and
its corresponding edited image as the optimization target, allowing for
user-defined manual edits. Next, we fine-tune the 2D editing model within the
GT view and across multiple views to align with the GT-edited image while
ensuring multi-view consistency. To meet the distinct requirements of GT view
fitting and multi-view consistency, we introduce separate LoRA modules for
targeted fine-tuning. Our approach delivers more consistent and controllable 2D
and 3D editing results than existing 2D-lifting-based methods, outperforming
them in both qualitative and quantitative evaluations.
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