no code implementations • 20 Dec 2023 • Octave Mariotti, Oisin Mac Aodha, Hakan Bilen
To address these limitations, we propose a new approach for semantic correspondence estimation that supplements discriminative self-supervised features with 3D understanding via a weak geometric spherical prior.
no code implementations • 5 Jun 2023 • Thomas Walker, Octave Mariotti, Amir Vaxman, Hakan Bilen
We introduce Explicit Neural Surfaces (ENS), an efficient smooth surface representation that directly encodes topology with a deformation field from a known base domain.
no code implementations • 1 Dec 2022 • Octave Mariotti, Oisin Mac Aodha, Hakan Bilen
We introduce ViewNeRF, a Neural Radiance Field-based viewpoint estimation method that learns to predict category-level viewpoints directly from images during training.
no code implementations • ICCV 2021 • Octave Mariotti, Oisin Mac Aodha, Hakan Bilen
Understanding the 3D world without supervision is currently a major challenge in computer vision as the annotations required to supervise deep networks for tasks in this domain are expensive to obtain on a large scale.
no code implementations • 2 Apr 2021 • Octave Mariotti, Hakan Bilen
There is a growing interest in developing computer vision methods that can learn from limited supervision.