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About this paper
Armen Avetisyan, Tatiana Khanova, Christopher Choy, Denver Dash, Angela Dai, Matthias Nießner
SceneCAD introduces an end-to-end framework that jointly optimizes CAD model alignments and planar layout estimation from RGB-D scans by learning object-object and object-layout relationships. This approach yields a measurable improvement in alignment accuracy on real-world data, producing globally consistent and lightweight 3D scene representations.
Key insights
- Jointly optimizing object alignments and scene layouts, guided by learning their inter-relationships, leads to more globally consistent and accurate 3D scene representations.
- The inherent coupling between objects and their surrounding scene layout is a crucial factor for robust full scene digitization and understanding.
- A lightweight, hierarchical approach can robustly predict planar scene layouts (corners, edges, quads) without relying on extensive heuristics.
Summary by alphaXiv.
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