C3Editor: Achieving Controllable Consistency in 2D Model for 3D Editing
This addresses inconsistency issues in 3D editing for users of 2D-lifting-based methods, representing an incremental improvement.
The paper tackles the problem of inconsistency in 2D-lifting-based 3D editing methods by proposing C3Editor, a framework that uses a view-consistent 2D editing model and selective optimization to achieve superior 3D editing results, outperforming existing methods in qualitative and quantitative evaluations.
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.