mlsanityData to 13 Oct 2026

Robust Rotation Synchronization via Low-rank and Sparse Matrix Decomposition

arXiv 1505.06079 ↗First posted 22 May 2015cs.CVcited by 8

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Abstract (arXiv)

This paper deals with the rotation synchronization problem, which arises in global registration of 3D point-sets and in structure from motion. The problem is formulated in an unprecedented way as a "low-rank and sparse" matrix decomposition that handles both outliers and missing data. A minimization strategy, dubbed R-GoDec, is also proposed and evaluated experimentally against state-of-the-art algorithms on simulated and real data. The results show that R-GoDec is the fastest among the robust algorithms.

Key facts. Cited by 8 papers in the map (data through 13 Oct 2026). First posted on arXiv 22 May 2015.

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Citing papers per year: 2022: 1; 2023: 0; 2024: 5; 2025: 1; 2026: 1.

8 papers.