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Quentin De Smedt
Quentin De Smedt
LIFL, Université de Lille1
Verified email at telecom-lille.fr
Title
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Cited by
Year
Skeleton-based dynamic hand gesture recognition
Q De Smedt, H Wannous, JP Vandeborre
Proceedings of the IEEE conference on computer vision and pattern …, 2016
2722016
Shrec'17 track: 3d hand gesture recognition using a depth and skeletal dataset
Q De Smedt, H Wannous, JP Vandeborre, J Guerry, B Le Saux, D Filliat
3DOR-10th Eurographics Workshop on 3D Object Retrieval, 1-6, 2017
1322017
Heterogeneous hand gesture recognition using 3D dynamic skeletal data
Q De Smedt, H Wannous, JP Vandeborre
Computer Vision and Image Understanding 181, 60-72, 2019
702019
3d hand gesture recognition using a depth and skeletal dataset: Shrec'17 track
Q De Smedt, H Wannous, JP Vandeborre, J Guerry, BL Saux, D Filliat
Proceedings of the Workshop on 3D Object Retrieval, 33-38, 2017
662017
3D Hand Gesture Recognition by Analysing Set-of-Joints Trajectories
Q De Smedt, H Wannous, JP Vandeborre
2nd International Workshop on Understanding Human Activities through 3D …, 2016
302016
Dynamic hand gesture recognition-From traditional handcrafted to recent deep learning approaches
Q De Smedt
Université de Lille 1, Sciences et Technologies; CRIStAL UMR 9189, 2017
272017
Dynamic hand gesture recognition using skeleton-based features
Q De Smedt, H Wannous, JP Vandeborre
2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops …, 2016
52016
Reconnaisance de gestes dynamiques de la main-De la création de descripteurs aux récentes méthodes d’apprentissage profond
Q de Smedt
2017
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