Search Results for author:
Found 10 papers, 6 papers with code
Robust Group Synchronization via Cycle-Edge Message Passing
We then establish exact recovery and linear convergence guarantees for the proposed message passing procedure under a deterministic setting with adversarial corruption.
Message Passing Least Squares Framework and its Application to Rotation Synchronization
We propose an efficient algorithm for solving group synchronization under high levels of corruption and noise, while we focus on rotation synchronization.
Scalable Cluster-Consistency Statistics for Robust Multi-Object Matching
We develop new statistics for robustly filtering corrupted keypoint matches in the structure from motion pipeline.
Ab-initio Contrast Estimation and Denoising of Cryo-EM Images
We show that the contrast variability can be derived from the 2-D covariance matrix and we apply the existing Covariance Wiener Filtering (CWF) framework to estimate it.
Robust Group Synchronization via Quadratic Programming
We propose a novel quadratic programming formulation for estimating the corruption levels in group synchronization, and use these estimates to solve this problem.
Estimation of Camera Locations in Highly Corrupted Scenarios: All About that Base, No Shape Trouble
We propose a strategy for improving camera location estimation in structure from motion.
Exact Camera Location Recovery by Least Unsquared Deviations
We establish exact recovery for the Least Unsquared Deviations (LUD) algorithm of Ozyesil and Singer.
Robust Multi-object Matching via Iterative Reweighting of the Graph Connection Laplacian
We propose an efficient and robust iterative solution to the multi-object matching problem.
Message Passing Least Squares: A Unified Framework for Fast and Robust Group Synchronization
We propose an efficient algorithm for solving robust group synchronization given adversarially corrupted group ratios.
Fast, Accurate and Memory-Efficient Partial Permutation Synchronization
Previous partial permutation synchronization (PPS) algorithms, which are commonly used for multi-object matching, often involve computation-intensive and memory-demanding matrix operations.
