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Titlebook: Computer Vision – ECCV 2012; 12th European Confer Andrew Fitzgibbon,Svetlana Lazebnik,Cordelia Schmi Conference proceedings 2012 Springer-V

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21#
發(fā)表于 2025-3-25 04:33:36 | 只看該作者
A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustnesss from the maximum a-posteriori configuration. The model is evaluated on two challenging four-dimensional data sets from developmental biology. Compared to previous work, we obtain improved tracks due to an increased robustness against false positive detections and the incorporation of temporal domain knowledge.
22#
發(fā)表于 2025-3-25 07:45:41 | 只看該作者
Malcolm N. MacDonald,Duncan Hunterssing, such as noise removal and correct patch normalization, dramatically improves our results. Perhaps surprisingly, even better results are achieved on a variety of real test scenes by providing our algorithm with only . training depth data.
23#
發(fā)表于 2025-3-25 14:34:27 | 只看該作者
Studies in History and Philosophy of Scienceations: Eichner and Ferrari [5], Sapp .?[16], Andriluka . [2] and Yang and Ramanan [22]. We demonstrate that in each case the evaluator is able to predict if the algorithm has correctly estimated the pose or not.
24#
發(fā)表于 2025-3-25 18:55:42 | 只看該作者
Asylum Policy Responsiveness in Scandinaviag object trajectories and cast the relational weight learning task as an online latent SVM problem. Extensive experiments on challenging real world video sequences demonstrate the efficiency and effectiveness of our framework.
25#
發(fā)表于 2025-3-25 22:16:53 | 只看該作者
26#
發(fā)表于 2025-3-26 00:30:21 | 只看該作者
Patch Based Synthesis for Single Depth Image Super-Resolutionssing, such as noise removal and correct patch normalization, dramatically improves our results. Perhaps surprisingly, even better results are achieved on a variety of real test scenes by providing our algorithm with only . training depth data.
27#
發(fā)表于 2025-3-26 04:25:21 | 只看該作者
Has My Algorithm Succeeded? An Evaluator for Human Pose Estimatorsations: Eichner and Ferrari [5], Sapp .?[16], Andriluka . [2] and Yang and Ramanan [22]. We demonstrate that in each case the evaluator is able to predict if the algorithm has correctly estimated the pose or not.
28#
發(fā)表于 2025-3-26 11:06:26 | 只看該作者
Group Tracking: Exploring Mutual Relations for Multiple Object Trackingg object trajectories and cast the relational weight learning task as an online latent SVM problem. Extensive experiments on challenging real world video sequences demonstrate the efficiency and effectiveness of our framework.
29#
發(fā)表于 2025-3-26 13:32:52 | 只看該作者
30#
發(fā)表于 2025-3-26 18:09:03 | 只看該作者
Fast Regularization of Matrix-Valued Imageslarization of matrix valued images on a graphic processing unit..We demonstrate the effectiveness of our method for smoothing several group-valued image types, with applications in directions diffusion, motion analysis from depth sensors, and DT-MRI denoising.
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