no code implementations • 22 Apr 2024 • Sophia Sirko-Galouchenko, Alexandre Boulch, Spyros Gidaris, Andrei Bursuc, Antonin Vobecky, Patrick Pérez, Renaud Marlet
Models pretrained with our method exhibit improved BEV semantic segmentation performance, particularly in low-data scenarios.
no code implementations • NeurIPS 2023 • Antonin Vobecky, Oriane Siméoni, David Hurych, Spyros Gidaris, Andrei Bursuc, Patrick Pérez, Josef Sivic
We describe an approach to predict open-vocabulary 3D semantic voxel occupancy map from input 2D images with the objective of enabling 3D grounding, segmentation and retrieval of free-form language queries.
3D Semantic Occupancy Prediction 3D Semantic Segmentation +3
no code implementations • 18 Jul 2023 • Spyros Gidaris, Andrei Bursuc, Oriane Simeoni, Antonin Vobecky, Nikos Komodakis, Matthieu Cord, Patrick Pérez
Self-supervised learning can be used for mitigating the greedy needs of Vision Transformer networks for very large fully-annotated datasets.
1 code implementation • CVPR 2023 • Oriane Siméoni, Chloé Sekkat, Gilles Puy, Antonin Vobecky, Éloi Zablocki, Patrick Pérez
This way, the salient objects emerge as a by-product without any strong assumption on what an object should be.
1 code implementation • 21 Mar 2022 • Antonin Vobecky, David Hurych, Oriane Siméoni, Spyros Gidaris, Andrei Bursuc, Patrick Pérez, Josef Sivic
This work investigates learning pixel-wise semantic image segmentation in urban scenes without any manual annotation, just from the raw non-curated data collected by cars which, equipped with cameras and LiDAR sensors, drive around a city.
no code implementations • 4 Dec 2019 • Michal Uricar, Ganesh Sistu, Hazem Rashed, Antonin Vobecky, Varun Ravi Kumar, Pavel Krizek, Fabian Burger, Senthil Yogamani
We propose a novel GAN based algorithm for generating unseen patterns of soiled images.
1 code implementation • 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018) 2018 • Pavel Jahoda, Antonin Vobecky, Jan Cech, Jiri Matas
We propose a baseline method combining a deep convolutional neural network with an SVM.