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Yunpeng Shi

7 accepted papers

2025

Cycle-Sync: Robust Global Camera Pose Estimation through Enhanced Cycle-Consistent Synchronization

NeurIPS 2025spotlight

We introduce Cycle-Sync, a robust and global framework for estimating camera poses (both rotations and locations). Our core innovation is a location solver that adapts message-passing least squares (MPLS) - originally developed for group synchronization - to the camera localization setting. We modif…

Cited by 0SourceScholar
2024

Efficient Detection of Long Consistent Cycles and its Application to Distributed Synchronization

CVPR 2024poster

Group synchronization plays a crucial role in global pipelines for Structure from Motion (SfM). Its formulation is nonconvex and it is faced with highly corrupted measurements. Cycle consistency has been effective in addressing these challenges. However computationally efficient solutions are needed…

Cited by 1SourcePDFScholar
2020

Message Passing Least Squares Framework and its Application to Rotation Synchronization

ICML 2020poster

We propose an efficient algorithm for solving group synchronization under high levels of corruption and noise, while we focus on rotation synchronization. We first describe our recent theoretically guaranteed message passing algorithm that estimates the corruption levels of the measured group ratios…

Cited by 49SourcePDFScholar
2020

Robust Multi-Object Matching via Iterative Reweighting of the Graph Connection Laplacian

NeurIPS 2020poster

We propose an efficient and robust iterative solution to the multi-object matching problem. We first clarify serious limitations of current methods as well as the inappropriateness of the standard iteratively reweighted least squares procedure. In view of these limitations, we suggest a novel and mo…

Cited by 14SourcePDFScholar
2018

Estimation of Camera Locations in Highly Corrupted Scenarios: All About That Base, No Shape Trouble

CVPR 2018poster

We propose a strategy for improving camera location estimation in structure from motion. Our setting assumes highly corrupted pairwise directions (i.e., normalized relative location vectors), so there is a clear room for improving current state-of-the-art solutions for this problem. Our strategy ide…

Cited by 12SourcePDFScholar