Search Results for author: Huu Le

Found 24 papers, 11 papers with code

Depth Perspective-aware Multiple Object Tracking

no code implementations10 Jul 2022 Kha Gia Quach, Huu Le, Pha Nguyen, Chi Nhan Duong, Tien Dai Bui, Khoa Luu

This paper aims to tackle Multiple Object Tracking (MOT), an important problem in computer vision but remains challenging due to many practical issues, especially occlusions.

Depth Estimation Multiple Object Tracking

Fast Semantic-Assisted Outlier Removal for Large-scale Point Cloud Registration

no code implementations21 Feb 2022 Giang Truong, Huu Le, Alvaro Parra, Syed Zulqarnain Gilani, Syed M. S. Islam, David Suter

The volume of data to handle, and still elusive need to have the registration occur fully reliably and fully automatically, mean there is a need to innovate further.

Point Cloud Registration Semantic Segmentation

Escaping Poor Local Minima in Large Scale Robust Estimation

no code implementations22 Feb 2021 Huu Le, Christopher Zach

Robust parameter estimation is a crucial task in several 3D computer vision pipelines such as Structure from Motion (SfM).

Progressive Batching for Efficient Non-linear Least Squares

1 code implementation21 Oct 2020 Huu Le, Christopher Zach, Edward Rosten, Oliver J. Woodford

Non-linear least squares solvers are used across a broad range of offline and real-time model fitting problems.

Stochastic Optimization

A Graduated Filter Method for Large Scale Robust Estimation

1 code implementation CVPR 2020 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 contaminated by a large or unknown fraction of outliers.

Truncated Inference for Latent Variable Optimization Problems: Application to Robust Estimation and Learning

no code implementations ECCV 2020 Christopher Zach, Huu Le

Optimization problems with an auxiliary latent variable structure in addition to the main model parameters occur frequently in computer vision and machine learning.

BIG-bench Machine Learning

Hierarchical Encoding of Sequential Data With Compact and Sub-Linear Storage Cost

1 code implementation ICCV 2019 Huu Le, Ming Xu, Tuan Hoang, Michael Milford

We benchmark the performance of the proposed algorithm on several real-world benchmark datasets and experimentally validate the theoretical sub-linearity of our approach, while also showing that our approach yields competitive absolute storage performance as well.

Quantization Simultaneous Localization and Mapping +1

BTEL: A Binary Tree Encoding Approach for Visual Localization

no code implementations27 Jun 2019 Huu Le, Tuan Hoang, Michael Milford

Visual localization algorithms have achieved significant improvements in performance thanks to recent advances in camera technology and vision-based techniques.

Image Retrieval Quantization +2

SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences

1 code implementation6 Apr 2019 Huu Le, Thanh-Toan Do, Tuan Hoang, Ngai-Man Cheung

In particular, our work enables the use of randomized methods for point cloud registration without the need of putative correspondences.

Graph Matching Point Cloud Registration

SASSE: Scalable and Adaptable 6-DOF Pose Estimation

no code implementations5 Feb 2019 Huu Le, Tuan Hoang, Qianggong Zhang, Thanh-Toan Do, Anders Eriksson, Michael Milford

In this paper, we present a novel 6-DOF localization system that for the first time simultaneously achieves all the three characteristics: significantly sub-linear storage growth, agnosticism to image descriptors, and customizability to available storage and computational resources.

Benchmarking Pose Estimation +1

A Binary Optimization Approach for Constrained K-Means Clustering

1 code implementation24 Oct 2018 Huu Le, Anders Eriksson, Thanh-Toan Do, Michael Milford

This approach allows us to solve constrained K-Means where multiple types of constraints can be simultaneously enforced.

Large scale visual place recognition with sub-linear storage growth

1 code implementation23 Oct 2018 Huu Le, Michael Milford

Robotic and animal mapping systems share many of the same objectives and challenges, but differ in one key aspect: where much of the research in robotic mapping has focused on solving the data association problem, the grid cell neurons underlying maps in the mammalian brain appear to intentionally break data association by encoding many locations with a single grid cell neuron.

Chunking feature selection +1

Deterministic consensus maximization with biconvex programming

1 code implementation ECCV 2018 Zhipeng Cai, Tat-Jun Chin, Huu Le, David Suter

In this paper, we propose an efficient deterministic optimization algorithm for consensus maximization.

Binary Constrained Deep Hashing Network for Image Retrieval without Manual Annotation

no code implementations21 Feb 2018 Thanh-Toan Do, Tuan Hoang, Dang-Khoa Le Tan, Trung Pham, Huu Le, Ngai-Man Cheung, Ian Reid

However, training deep hashing networks for the task is challenging due to the binary constraints on the hash codes, the similarity preserving property, and the requirement for a vast amount of labelled images.

Image Retrieval Quantization +1

Simultaneous Compression and Quantization: A Joint Approach for Efficient Unsupervised Hashing

no code implementations19 Feb 2018 Tuan Hoang, Thanh-Toan Do, Huu Le, Dang-Khoa Le-Tan, Ngai-Man Cheung

For unsupervised data-dependent hashing, the two most important requirements are to preserve similarity in the low-dimensional feature space and to minimize the binary quantization loss.

Image Retrieval Quantization +1

From Selective Deep Convolutional Features to Compact Binary Representations for Image Retrieval

1 code implementation7 Feb 2018 Thanh-Toan Do, Tuan Hoang, Dang-Khoa Le Tan, Huu Le, Tam V. Nguyen, Ngai-Man Cheung

In the large-scale image retrieval task, the two most important requirements are the discriminability of image representations and the efficiency in computation and storage of representations.

Image Retrieval Retrieval

Deterministic Approximate Methods for Maximum Consensus Robust Fitting

1 code implementation27 Oct 2017 Huu Le, Tat-Jun Chin, Anders Eriksson, Thanh-Toan Do, David Suter

Further, our approach is naturally applicable to estimation problems with geometric residuals

An Exact Penalty Method for Locally Convergent Maximum Consensus

no code implementations CVPR 2017 Huu Le, Tat-Jun Chin, David Suter

Our method is based on a formulating the problem with linear complementarity constraints, then defining a penalized version which is provably equivalent to the original problem.

Conformal Surface Alignment With Optimal Mobius Search

no code implementations CVPR 2016 Huu Le, Tat-Jun Chin, David Suter

Deformations of surfaces with the same intrinsic shape can often be described accurately by a conformal model.

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