Search Results for author: Anders Eriksson

Found 26 papers, 6 papers with code

Learning Compositional Shape Priors for Few-Shot 3D Reconstruction

no code implementations11 Jun 2021 Mateusz Michalkiewicz, Stavros Tsogkas, Sarah Parisot, Mahsa Baktashmotlagh, Anders Eriksson, Eugene Belilovsky

The impressive performance of deep convolutional neural networks in single-view 3D reconstruction suggests that these models perform non-trivial reasoning about the 3D structure of the output space.

3D Reconstruction Few-Shot Learning +1

Rotation Coordinate Descent for Fast Globally Optimal Rotation Averaging

no code implementations CVPR 2021 Álvaro Parra, Shin-Fang Chng, Tat-Jun Chin, Anders Eriksson, Ian Reid

Under mild conditions on the noise level of the measurements, rotation averaging satisfies strong duality, which enables global solutions to be obtained via semidefinite programming (SDP) relaxation.

Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors

1 code implementation ECCV 2020 Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders Eriksson, Eugene Belilovsky

In this work we demonstrate experimentally that naive baselines do not apply when the goal is to learn to reconstruct novel objects using very few examples, and that in a \emph{few-shot} learning setting, the network must learn concepts that can be applied to new categories, avoiding rote memorization.

3D Reconstruction Few-Shot Learning +2

Implicitly Defined Layers in Neural Networks

no code implementations3 Mar 2020 Qianggong Zhang, Yanyang Gu, Michalkiewicz Mateusz, Mahsa Baktashmotlagh, Anders Eriksson

In conventional formulations of multilayer feedforward neural networks, the individual layers are customarily defined by explicit functions.

Visual SLAM: Why Bundle Adjust?

no code implementations11 Feb 2019 Álvaro Parra, Tat-Jun Chin, Anders Eriksson, Ian Reid

Bundle adjustment plays a vital role in feature-based monocular SLAM.

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.

Pose Estimation Visual Localization

Star Tracking using an Event Camera

2 code implementations7 Dec 2018 Tat-Jun Chin, Samya Bagchi, Anders Eriksson, Andre van Schaik

Star trackers are primarily optical devices that are used to estimate the attitude of a spacecraft by recognising and tracking star patterns.

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.

Maximum Consensus Parameter Estimation by Reweighted $\ell_1$ Methods

no code implementations22 Mar 2018 Pulak Purkait, Christopher Zach, Anders Eriksson

Robust parameter estimation in computer vision is frequently accomplished by solving the maximum consensus (MaxCon) problem.

Image2Mesh: A Learning Framework for Single Image 3D Reconstruction

1 code implementation29 Nov 2017 Jhony K. Pontes, Chen Kong, Sridha Sridharan, Simon Lucey, Anders Eriksson, Clinton Fookes

One challenge that remains open in 3D deep learning is how to efficiently represent 3D data to feed deep networks.

3D Reconstruction

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

Rotation Averaging and Strong Duality

no code implementations CVPR 2018 Anders Eriksson, Carl Olsson, Fredrik Kahl, Tat-Jun Chin

In this paper we explore the role of duality principles within the problem of rotation averaging, a fundamental task in a wide range of computer vision applications.

Structure from Motion

Richardson-Lucy Deblurring for Moving Light Field Cameras

no code implementations14 Jun 2016 Donald G. Dansereau, Anders Eriksson, Jürgen Leitner

The method deals correctly with blur caused by 6-degree-of-freedom camera motion in complex 3-D scenes, without performing depth estimation.

Deblurring Depth Estimation

A Consensus-Based Framework for Distributed Bundle Adjustment

no code implementations CVPR 2016 Anders Eriksson, John Bastian, Tat-Jun Chin, Mats Isaksson

In this paper we study large-scale optimization problems in multi-view geometry, in particular the Bundle Adjustment problem.

Structure from Motion

Guaranteed Outlier Removal With Mixed Integer Linear Programs

no code implementations CVPR 2016 Tat-Jun Chin, Yang Heng Kee, Anders Eriksson, Frank Neumann

Towards the goal of solving maximum consensus exactly, we present guaranteed outlier removal as a technique to reduce the runtime of exact algorithms.

Global Optimization

Non-linear Dimensionality Regularizer for Solving Inverse Problems

no code implementations16 Mar 2016 Ravi Garg, Anders Eriksson, Ian Reid

Additionally, we evaluate our method on the challenging problem of Non-Rigid Structure from Motion and our approach delivers promising results on CMU mocap dataset despite the presence of significant occlusions and noise.

Structure from Motion

The k-Support Norm and Convex Envelopes of Cardinality and Rank

no code implementations CVPR 2015 Anders Eriksson, Trung Thanh Pham, Tat-Jun Chin, Ian Reid

Sparsity, or cardinality, as a tool for feature selection is extremely common in a vast number of current computer vision applications.

Feature Selection

Efficient Globally Optimal Consensus Maximisation With Tree Search

no code implementations CVPR 2015 Tat-Jun Chin, Pulak Purkait, Anders Eriksson, David Suter

We aim to change this state of affairs by proposing a very efficient algorithm for global maximisation of consensus.

Pseudoconvex Proximal Splitting for L-infty Problems in Multiview Geometry

no code implementations CVPR 2014 Anders Eriksson, Mats Isaksson

In this paper we study optimization methods for minimizing large-scale pseudoconvex L_infinity problems in multiview geometry.

Fast Convolutional Sparse Coding

no code implementations CVPR 2013 Hilton Bristow, Anders Eriksson, Simon Lucey

Sparse coding has become an increasingly popular method in learning and vision for a variety of classification, reconstruction and coding tasks.

General Classification

Visualizing Sentiment Analysis on a User Forum

no code implementations LREC 2012 Rasmus Sundberg, Anders Eriksson, Johan Bini, Pierre Nugues

Sentiment analysis, or opinion mining, is the process of extracting sentiment from documents or sentences, where the expressed sentiment is typically categorized as positive, negative, or neutral.

Opinion Mining Question Answering +1

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