Welcome to my personal homepage!

research highlights

I received the Best Science Paper Award at BMVC 2018 and DST Award at DICTA 2017.

Here are links to my Google Scholar, Research Gate, and my Github.

Selected Publications

Huu Le, Christopher Zach - "Robust Fitting with Truncated Least Squares: A Bilevel Optimization Approach" (3DV) 2021 (Source)

Giang Truong, Huu Le, David Suter, Erchuan Zhang, Syed Zulqarnain Gilani - "Unsupervised Learning for Robust Fitting: A Reinforcement Learning Approach", in Computer Vision and Pattern Recognition (CVPR) 2021.

Huu Le, Christopher Zach, Edward Rosten, Oliver J. Woodford - "Progressive Batching for Efficient Non-linear Least Squares" (ACCV) 2020 - Oral

Huu Le, Christopher Zach - "A Graduated Filter Method for Large Scale Robust Estimation", in Computer Vision and Pattern Recognition (CVPR) 2020.

Huu Le, Tat-Jun Chin, Anders Eriksson, Thanh-Toan Do, David Suter - "Deterministic Approximate Methods for Maximum Consensus Robust Fitting" - IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).

Huu Le, Ming Xu, Tuan Hoang and Michael Milford - "Hierarchical Encoding of Sequential Data with Compact and Sub-linear Storage Cost", International Conference on Computer Vision (ICCV) 2019.

Huu Le, Tuan Hoang, and Michael Milford - "BTEL: A Binary Tree Encoding Approach for Visual Localization", International Conference on Intelligent Robots and Systems (IROS) 2019.

Huu Le, Thanh-Toan Do, Tuan Hoang, and Ngai-Man Cheung - "SDRSAC: A Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences", in Computer Vision and Pattern Recognition (CVPR) 2019 - Oral Presentation, Best Paper Finalist.

Huu Le, Anders Eriksson, Thanh-Toan Do and Michael Milford - "A Binary Optimization Approach for Constrained K-Means Clustering", in Asian Conference on Computer Vision (ACCV) 2018.

Huu Le, Anders Eriksson, Michael Milford, Thanh-Toan Do, Tat-Jun Chin and David Suter, "Non-smooth M-estimator for Maximum Consensus Estimation" - at 29th British Machine Vision Conference (BMVC) 2018 - Oral Presentation - Best Science Paper Award.

Huu Le, Tat-Jun Chin and David Suter, "An Exact Penalty Method for Locally Convergent Maximum Consensus", Computer Vision and Pattern Recognition (CVPR) 2017.

Huu Le, Tat-Jun Chin and David Suter, "RATSAC - Random Tree Sampling for Maximum Consensus Estimation", In Digital Image Computing: Techniques and Applications (DICTA), 2017 - Oral Presentation - DST Best Paper Award.

Huu Le, Tat-Jun Chin and David Suter, "Conformal Surface Alignment With Optimal Mobius Search", Computer Vision and Pattern Recognition (CVPR) 2016.

Email: Before@: huulem After@: outlook.com