Výsledky vyhledávání - "Giorgia Pitteri"

3D Object Detection and Pose Estimation of Unseen Objects in Color Images with Local Surface Embeddings

Autor: Giorgia Pitteri, Slobodan Ilic, Vincent Lepetit, Aurélie Bugeau

Publikováno v: 15th Asian Conference on Computer Vision
15th Asian Conference on Computer Vision, Nov 2020, Kyoto (virtual conference), Japan
Computer Vision – ACCV 2020 ISBN: 9783030695248
ACCV (1)
HAL

International audience; We present an approach for detecting and estimating the 3D poses of objects in images that requires only an untextured CAD model and no training phase for new objects. Our approach combines Deep Learning and 3D geometry: It re

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::450a1b27f4119b51d9eb35361a1316a1
https://hal.archives-ouvertes.fr/hal-02961991v1/document

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On Object Symmetries and 6D Pose Estimation from Images

Autor: Giorgia Pitteri, Slobodan Ilic, Michael Ramamonjisoa, Vincent Lepetit

Publikováno v: 3DV
3DV, 2019, Québec, Canada

Objects with symmetries are common in our daily life and in industrial contexts, but are often ignored in the recent literature on 6D pose estimation from images. In this paper, we study in an analytical way the link between the symmetries of a 3D ob

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7ea0b8e814961bbe308548443365d0a
https://doi.org/10.1109/3dv.2019.00073

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CorNet: Generic 3D Corners for 6D Pose Estimation of New Objects without Retraining

Autor: Slobodan Ilic, Vincent Lepetit, Giorgia Pitteri

Publikováno v: ICCV Workshops

We present a novel approach to the detection and 3D pose estimation of objects in color images. Its main contribution is that it does not require any training phases nor data for new objects, while state-of-the-art methods typically require hours of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a158218f3161b4b06b4e740c45f78030
http://arxiv.org/abs/1908.11457

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Depth-based frontal view generation for pose invariant face recognition with consumer RGB-D sensors

Autor: Giorgia Pitteri, Matteo Munaro, Emanuele Menegatti

Publikováno v: Intelligent Autonomous Systems 14 ISBN: 9783319480350
IAS

In this work, we propose to exploit depth information to build a pose-invariant face recognition algorithm from RGB-D data. Our approach first estimates the head pose and then generates a frontal view for those faces that are rotated with respect to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff49981e76f20aadc2c7d26c754de488
http://hdl.handle.net/11577/3389575

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