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Conference papers

Deep MANTA: A Coarse-to-Fine Many-Task Network for Joint 2D and 3D Vehicle Analysis from Monocular Image

Florian Chabot 1 Mohamed Chaouch 1 Jaonary Rabarisoa 1 Céline Teulière 2, 3 Thierry Chateau 2, 3 
1 LVIC - Laboratoire Vision et Ingénierie des Contenus
DIASI - Département Intelligence Ambiante et Systèmes Interactifs : DRT/LIST/DIASI
3 COMSEE - COMputers that SEE
ISPR - Image, système de perception, robotique
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01653519
Contributor : Thierry Chateau Connect in order to contact the contributor
Submitted on : Friday, December 1, 2017 - 3:15:24 PM
Last modification on : Thursday, February 17, 2022 - 10:08:04 AM

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  • HAL Id : hal-01653519, version 1

Citation

Florian Chabot, Mohamed Chaouch, Jaonary Rabarisoa, Céline Teulière, Thierry Chateau. Deep MANTA: A Coarse-to-Fine Many-Task Network for Joint 2D and 3D Vehicle Analysis from Monocular Image. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, Honolulu, United States. ⟨hal-01653519⟩

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