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POSITION: Open World 3D Scene CAD Recomposition
Summary
This study introduces POSITION, a novel method for 3D scene reconstruction using open-world CAD retrieval. It effectively generalizes to diverse scenes by decomposing the task into object representation, retrieval, and pose alignment.
Area of Science:
- Computer Vision
- 3D Reconstruction
- Computational Geometry
Background:
- 3D scene CAD recomposition reconstructs environments using CAD models.
- Current methods struggle with generalization due to limited training data.
- Reconstructing diverse real-world scenes remains a challenge.
Purpose of the Study:
- To develop an open-world 3D scene CAD recomposition method.
- To improve generalization to diverse scenes and scalable CAD databases.
- To accurately simulate geometric properties and spatial arrangements of original environments.
Main Methods:
- POSITION employs a divide-and-conquer strategy.
- Extracts open-world multi-modal object representations from 3D scenes.
- Utilizes coarse-to-fine retrieval for visually, geometrically, and semantically matching CADs.
- Applies physically plausible pose alignment for consistent geometry and layout.
Main Results:
- Achieves generalization across various scene types and scalable CAD databases without retraining.
- Demonstrates superior CAD recomposition performance on Scan2CAD and real-world datasets.
- Successfully reconstructs 3D scenes with CADs from an open-set database.
Conclusions:
- POSITION offers a robust solution for open-world 3D scene CAD recomposition.
- The method overcomes limitations of existing scan-to-CAD approaches.
- Enables accurate simulation of geometric properties and spatial arrangements in diverse environments.
