1 code implementation • 9 Apr 2024 • Axel Barroso-Laguna, Sowmya Munukutla, Victor Adrian Prisacariu, Eric Brachmann
Usually, correspondences are 2D-to-2D and the pose we estimate is defined only up to scale.
1 code implementation • CVPR 2023 • Axel Barroso-Laguna, Eric Brachmann, Victor Adrian Prisacariu, Gabriel J. Brostow, Daniyar Turmukhambetov
As a remedy, we propose the Fundamental Scoring Network (FSNet), which infers a score for a pair of overlapping images and any proposed fundamental matrix.
1 code implementation • CVPR 2022 • Axel Barroso-Laguna, Yurun Tian, Krystian Mikolajczyk
We formulate the scale estimation problem as a prediction of a probability distribution over scale factors.
1 code implementation • NeurIPS 2020 • Yurun Tian, Axel Barroso-Laguna, Tony Ng, Vassileios Balntas, Krystian Mikolajczyk
Recent works show that local descriptor learning benefits from the use of L2 normalisation, however, an in-depth analysis of this effect lacks in the literature.
no code implementations • 27 May 2020 • Yurun Tian, Vassileios Balntas, Tony Ng, Axel Barroso-Laguna, Yiannis Demiris, Krystian Mikolajczyk
In this paper, we present a novel approach that exploits the information within the descriptor space to propose keypoint locations.
1 code implementation • 12 May 2020 • Axel Barroso-Laguna, Yannick Verdie, Benjamin Busam, Krystian Mikolajczyk
Local feature extraction remains an active research area due to the advances in fields such as SLAM, 3D reconstructions, or AR applications.
3 code implementations • ICCV 2019 • Axel Barroso-Laguna, Edgar Riba, Daniel Ponsa, Krystian Mikolajczyk
We introduce a novel approach for keypoint detection task that combines handcrafted and learned CNN filters within a shallow multi-scale architecture.
Ranked #5 on Image Matching on IMC PhotoTourism (using extra training data)