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Markov-based Silhouette Extraction for Three--Dimensional Body Tracking in Presence of Cluttered Background.

, , , and . BMVC, page 1-10. BMVA Press, (2004)

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On Pre-Trained Image Features and Synthetic Images for Deep Learning., , , and . CoRR, (2017)ALCN: Meta-Learning for Contrast Normalization Applied to Robust 3D Pose Estimation., , and . CoRR, (2017)Feature Mapping for Learning Fast and Accurate 3D Pose Inference from Synthetic Images., , and . CoRR, (2017)Fast Keypoint Recognition Using Random Ferns., , , and . IEEE Trans. Pattern Anal. Mach. Intell., 32 (3): 448-461 (2010)DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo., , and . IEEE Trans. Pattern Anal. Mach. Intell., 32 (5): 815-830 (2010)Registration methods for harmonious integration of real worlds and computer generated objects., , and . Eurographics (Short Presentations), Eurographics Association, (1999)Pose-specific non-linear mappings in feature space towards multiview facial expression recognition., , , and . Image Vis. Comput., (2017)EPnP: An Accurate O(n) Solution to the PnP Problem., , and . Int. J. Comput. Vis., 81 (2): 155-166 (2009)SharpNet: Fast and Accurate Recovery of Occluding Contours in Monocular Depth Estimation., and . ICCV Workshops, page 2109-2118. IEEE, (2019)LU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-Net., , , , and . ICCV Workshops, page 942-950. IEEE, (2019)