1 code implementation • 8 May 2024 • Aimira Baitieva, David Hurych, Victor Besnier, Olivier Bernard
Acknowledging that traditional AD methods struggle with this dataset, we introduce (2) Segmentation-based Anomaly Detector (SegAD).
no code implementations • 12 Apr 2024 • Patrik Vacek, David Hurych, Tomáš Svoboda, Karel Zimmermann
We identified the structural constraints and the use of large and strict rigid clusters as the main pitfall of the current approaches and we propose a novel clustering approach that allows for combination of overlapping soft clusters as well as non-overlapping rigid clusters representation.
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
1 code implementation • 12 Dec 2023 • Patrik Vacek, David Hurych, Karel Zimmermann, Patrick Perez, Tomas Svoboda
Learning without supervision how to predict 3D scene flows from point clouds is essential to many perception systems.
1 code implementation • 15 Sep 2023 • Awet Haileslassie Gebrehiwot, David Hurych, Karel Zimmermann, Patrick Pérez, Tomáš Svoboda
Deep perception models have to reliably cope with an open-world setting of domain shifts induced by different geographic regions, sensor properties, mounting positions, and several other reasons.
1 code implementation • 13 Jul 2022 • Awet Haileslassie Gebrehiwot, Patrik Vacek, David Hurych, Karel Zimmermann, Patrick Perez, Tomáš Svoboda
We propose to leverage sequences of point clouds to boost the pseudolabeling technique in a teacher-student setup via training multiple teachers, each with access to different temporal information.
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.
1 code implementation • 15 Dec 2020 • Antonín Vobecký, David Hurych, Michal Uřičář, Patrick Pérez, Josef Šivic
This is achieved with a data generator (called DummyNet) with disentangled control of the pose, the appearance, and the target background scene.
no code implementations • 9 Feb 2019 • Michal Uricar, Pavel Krizek, David Hurych, Ibrahim Sobh, Senthil Yogamani, Patrick Denny
Generative Adversarial Networks (GAN) have gained a lot of popularity from their introduction in 2014 till present.
no code implementations • 26 Jan 2019 • Michal Uricar, David Hurych, Pavel Krizek, Senthil Yogamani
There is a large gap between academic and industrial setting and a substantial way from a research prototype, built on public datasets, to a deployable solution which is a challenging task.