3D Scene Change Detection with Consistent Multi-View Aggregation
Published:Dec 28, 2025 08:00
•1 min read
•ArXiv
Analysis
This paper addresses the problem of 3D scene change detection, a crucial task for scene monitoring and reconstruction. It tackles the limitations of existing methods, such as spatial inconsistency and the inability to separate pre- and post-change states. The proposed SCaR-3D framework, leveraging signed-distance-based differencing and multi-view aggregation, aims to improve accuracy and efficiency. The contribution of a new synthetic dataset (CCS3D) for controlled evaluations is also significant.
Key Takeaways
- •Proposes SCaR-3D, a new framework for 3D scene change detection.
- •Addresses spatial inconsistency and separation of pre- and post-change states.
- •Utilizes signed-distance-based differencing and multi-view aggregation.
- •Introduces a new synthetic dataset (CCS3D) for evaluation.
- •Demonstrates high accuracy and efficiency compared to existing methods.
Reference
“SCaR-3D, a novel 3D scene change detection framework that identifies object-level changes from a dense-view pre-change image sequence and sparse-view post-change images.”