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Titlebook: Computer Vision – ECCV 2016; 14th European Confer Bastian Leibe,Jiri Matas,Max Welling Conference proceedings 2016 Springer International P

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11#
發(fā)表于 2025-3-23 10:09:29 | 只看該作者
12#
發(fā)表于 2025-3-23 16:58:45 | 只看該作者
13#
發(fā)表于 2025-3-23 21:52:50 | 只看該作者
https://doi.org/10.1007/978-3-030-32843-6ving for each pose individually, the trajectory can be considered as a generalized camera. Thus, all poses can be jointly estimated by solving a generalized P.P (gP.P) problem. In this paper, we show that the gP.P problem for camera trajectories permits an extremely efficient minimal solution when e
14#
發(fā)表于 2025-3-24 02:12:26 | 只看該作者
https://doi.org/10.1007/978-3-030-32843-6 hidden layer to directly output the binary codes. This addresses a challenging issue in some previous works: optimizing non-smooth objective functions due to binarization. Moreover, we incorporate independence and balance properties in the direct and strict forms in the learning. Furthermore, we in
15#
發(fā)表于 2025-3-24 05:08:13 | 只看該作者
16#
發(fā)表于 2025-3-24 07:06:11 | 只看該作者
17#
發(fā)表于 2025-3-24 11:10:58 | 只看該作者
Homeostasis and the Maintenance of Integritya ball, an autonomous car should recognize what is going on and respond immediately. This is a very challenging problem for four reasons. First, only partial actions are observed. Second, there is a large variability in negative data. Third, the start of the action is unknown, so it is unclear over
18#
發(fā)表于 2025-3-24 18:54:11 | 只看該作者
19#
發(fā)表于 2025-3-24 22:28:22 | 只看該作者
https://doi.org/10.1007/978-3-319-46454-1computational photography; image classification; particle swarm optimization; pattern mining; semantic c
20#
發(fā)表于 2025-3-25 00:44:32 | 只看該作者
978-3-319-46453-4Springer International Publishing AG 2016
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