Adaptive Scaling with Geometric and Visual Continuity of completed 3D objects
Application Category
📝 Abstract
Object completion networks typically produce static Signed Distance Fields (SDFs) that faithfully reconstruct geometry but cannot be rescaled or deformed without introducing structural distortions. This limitation restricts their use in applications requiring flexible object manipulation, such as indoor redesign, simulation, and digital content creation. We introduce a part-aware scaling framework that transforms these static completed SDFs into editable, structurally coherent objects. Starting from SDFs and Texture Fields generated by state-of-the-art completion models, our method performs automatic part segmentation, defines user-controlled scaling zones, and applies smooth interpolation of SDFs, color, and part indices to enable proportional and artifact-free deformation. We further incorporate a repetition-based strategy to handle large-scale deformations while preserving repeating geometric patterns. Experiments on Matterport3D and ShapeNet objects show that our method overcomes the inherent rigidity of completed SDFs and is visually more appealing than global and naive selective scaling, particularly for complex shapes and repetitive structures.
Problem
Research questions and friction points this paper is trying to address.
3D object completion
Signed Distance Field
object scaling
geometric deformation
structural distortion
Innovation
Methods, ideas, or system contributions that make the work stand out.
part-aware scaling
Signed Distance Field
geometric continuity
adaptive deformation
repetition preservation
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