I am a research scientist at Facebook AI Research since September 2018, with a focus on computer vision and machine learning. I am also Associate Professor at the University of Oxford, specialising on the same topics.
Interests
I am interested in deep image representations for computer vision, with applications to image understanding and 3D reconstruction. I am also interested in unsupervised learning and in the interpretability of black box models.
Related Links
Latest Publications
CVPR - June 18, 2021
Discovering Relationships between Object Categories via Universal Canonical Maps
Natalia Neverova, Artsiom Sanakoyeu, Patrick Labatut, David Novotny, Andrea Vedaldi
CVPR - June 18, 2021
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go
Marvin Eisenberger, David Novotny, Gael Kerchenbaum, Patrick Labatut, Natalia Neverova, Daniel Cremers, Andrea Vedaldi
CVPR - June 17, 2021
Unsupervised Learning of 3D Object Categories from Videos in the Wild
Philipp Henzler, Jeremy Reizenstein, Patrick Labatut, Roman Shapovalov, Tobias Ritschel, Andrea Vedaldi, David Novotny
ICLR - May 3, 2021
Support-Set Bottlenecks for Video-Text Representation Learning
Mandela Patrick, Po-Yao Huang, Florian Metze, Andrea Vedaldi, Alexander Hauptmann, Yuki M. Asano, João Henriques
NeurIPS - December 7, 2020
Labelling unlabelled videos from scratch with multi-modal self-supervision
Yuki M. Asano, Mandela Patrick, Christian Rupprecht, Andrea Vedaldi
NeurIPS - December 1, 2020
Continuous Surface Embeddings
Natalia Neverova, David Novotny, Vasil Khalidov, Marc Szafraniec, Patrick Labatut, Andrea Vedaldi
CVPR - May 31, 2020
Transferring Dense Pose to Proximal Animal Classes
Artsiom Sanakoyeu, Vasil Khalidov, Maureen S. McCarthy, Andrea Vedaldi, Natalia Neverova
NeurIPS - December 9, 2019
Fixing the train-test resolution discrepancy
Hugo Touvron, Andrea Vedaldi, Matthijs Douze, Hervé Jégou
NeurIPS - November 17, 2019
Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels
Natalia Neverova, David Novotny, Andrea Vedaldi
ICCV Workshop on Interpreting and Explaining Visual AI Models - October 20, 2019
Occlusions for Effective Data Augmentation in Image Classification
Ruth Fong, Andrea Vedaldi
ICCV - October 20, 2019
Understanding Deep Networks via Extremal Perturbations and Smooth Masks
Ruth Fong, Mandela Patrick, Andrea Vedaldi
ICCV - September 5, 2019
C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion
David Novotny, Nikhila Ravi, Benjamin Graham, Natalia Neverova, Andrea Vedaldi
CVPR - June 9, 2019
Slim DensePose: Thrifty Learning from Sparse Annotations and Motion Cues
Natalia Neverova, James Thewlis, Riza Alp Guler, Iasonas Kokkinos, Andrea Vedaldi
Videos
All Videos
Transferring Dense Pose to Proximal Animal Classes
| June 10, 2020