no code implementations • 11 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.
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.
no code implementations • 2 Dec 2020 • Dominic Jack, Frederic Maire, Simon Denman, Anders Eriksson
Image convolutions have been a cornerstone of a great number of deep learning advances in computer vision.
no code implementations • 10 May 2020 • Mateusz Michalkiewicz, Eugene Belilovsky, Mahsa Baktashmotlagh, Anders Eriksson
Deep learning applied to the reconstruction of 3D shapes has seen growing interest.
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.
no code implementations • 3 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.
no code implementations • 11 Feb 2019 • Álvaro Parra, Tat-Jun Chin, Anders Eriksson, Ian Reid
Bundle adjustment plays a vital role in feature-based monocular SLAM.
no code implementations • 5 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.
no code implementations • 21 Jan 2019 • Mateusz Michalkiewicz, Jhony K. Pontes, Dominic Jack, Mahsa Baktashmotlagh, Anders Eriksson
This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"
2 code implementations • 7 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.
1 code implementation • 24 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.
1 code implementation • 29 Mar 2018 • Dominic Jack, Jhony K. Pontes, Sridha Sridharan, Clinton Fookes, Sareh Shirazi, Frederic Maire, Anders Eriksson
Representing 3D shape in deep learning frameworks in an accurate, efficient and compact manner still remains an open challenge.
no code implementations • 22 Mar 2018 • Pulak Purkait, Christopher Zach, Anders Eriksson
Robust parameter estimation in computer vision is frequently accomplished by solving the maximum consensus (MaxCon) problem.
1 code implementation • 29 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.
1 code implementation • 27 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
no code implementations • 23 Jul 2017 • Jhony K. Pontes, Chen Kong, Anders Eriksson, Clinton Fookes, Sridha Sridharan, Simon Lucey
3D reconstruction from 2D images is a central problem in computer vision.
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.
no code implementations • 14 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.
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.
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.
no code implementations • 16 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.
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.
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.
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.
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.
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.