6 citations · 10 across the 6 of their papers we have counts for
15 papers
Fast Semantic-Assisted Outlier Removal for Large-scale Point Cloud Registration
Giang Truong, Huu Le, Alvaro Parra +3
With current trends in sensors (cheaper, more volume of data) and applications (increasing affordability for new tasks, new ideas in what 3D data could be useful for); there is cor…
DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking
Kha Gia Quach, Pha Nguyen, Huu Le +4
Multi-Camera Multiple Object Tracking (MC-MOT) is a significant computer vision problem due to its emerging applicability in several real-world applications. Despite a large number…
Unsupervised Learning for Robust Fitting:A Reinforcement Learning Approach
Giang Truong, Huu Le, David Suter +2
Robust model fitting is a core algorithm in a large number of computer vision applications. Solving this problem efficiently for datasets highly contaminated with outliers is, howe…
Escaping Poor Local Minima in Large Scale Robust Estimation
Huu Le, Christopher Zach
Robust parameter estimation is a crucial task in several 3D computer vision pipelines such as Structure from Motion (SfM). State-of-the-art algorithms for robust estimation, howeve…
Progressive Batching for Efficient Non-linear Least Squares
Huu Le, Christopher Zach, Edward Rosten +1
Non-linear least squares solvers are used across a broad range of offline and real-time model fitting problems. Most improvements of the basic Gauss-Newton algorithm tackle converg…
A Graduated Filter Method for Large Scale Robust Estimation
Huu Le, Christopher Zach
Due to the highly non-convex nature of large-scale robust parameter estimation, avoiding poor local minima is challenging in real-world applications where input data is contaminate…