Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Ramy Battrawy"'
Publikováno v:
Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::036c8bb61a23eeecab6dae8b196b4aa5
https://doi.org/10.5220/0011615900003411
https://doi.org/10.5220/0011615900003411
The proposed RMS-FlowNet is a novel end-to-end learning-based architecture for accurate and efficient scene flow estimation which can operate on point clouds of high density. For hierarchical scene flow estimation, the existing methods depend on eith
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::071f195242e369991f1096f35a6d2649
Publikováno v:
IROS
Scene flow is the dense 3D reconstruction of motion and geometry of a scene. Most state-of-the-art methods use a pair of stereo images as input for full scene reconstruction. These methods depend a lot on the quality of the RGB images and perform poo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::972e10b389e82b0987b86e52113b07b7
https://doi.org/10.1109/iros45743.2020.9341077
https://doi.org/10.1109/iros45743.2020.9341077
Publikováno v:
ITSC
In this paper, we propose deepRGBXYZ – a feature descriptor to represent pixels for robust dense pixel matching. To this end, we concatenate RGB image (appearance) information with the depth (geometric) information represented as XYZ in order to bu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa9479b5503e0cfd264fac4c3b9a3c2f
https://doi.org/10.1109/itsc45102.2020.9294195
https://doi.org/10.1109/itsc45102.2020.9294195
Publikováno v:
IROS
We propose a new approach called LiDAR-Flow to robustly estimate a dense scene flow by fusing a sparse LiDAR with stereo images. We take the advantage of the high accuracy of LiDAR to resolve the lack of information in some regions of stereo images d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7800a059e4335f4da045efa2a3310d2e
http://arxiv.org/abs/1910.14453
http://arxiv.org/abs/1910.14453