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Learning to Efficiently Detect Repeatable Interest Points in Depth Data.

, , and . ECCV (1), volume 7572 of Lecture Notes in Computer Science, page 200-213. Springer, (2012)

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Efficient Dense Stereo with Occlusions for New View-Synthesis by Four-State Dynamic Programming., , , , and . International Journal of Computer Vision, 71 (1): 89-110 (2007)TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context., , , and . International Journal of Computer Vision, 81 (1): 2-23 (2009)Synthetic training in object detection., , , , , , and . ICIP, page 3113-3117. IEEE, (2013)Real-time human pose recognition in parts from single depth images., , , , , , , and . CVPR, page 1297-1304. IEEE Computer Society, (2011)Depth-Based Hand Pose Estimation: Data, Methods, and Challenges., , , , and . ICCV, page 1868-1876. IEEE Computer Society, (2015)Guest Editors' Introduction to the Special Issue on Multimodal Human Pose Recovery and Behavior Analysis., , , and . IEEE Trans. Pattern Anal. Mach. Intell., 38 (8): 1489-1491 (2016)RetroDepth: 3D silhouette sensing for high-precision input on and above physical surfaces., , , , , , , , , and 3 other author(s). CHI, page 1377-1386. ACM, (2014)Learning a Generative Model of Images by Factoring Appearance and Shape., , , and . Neural Computation, 23 (3): 593-650 (2011)Entangled Decision Forests and Their Application for Semantic Segmentation of CT Images., , , , , and . IPMI, volume 6801 of Lecture Notes in Computer Science, page 184-196. Springer, (2011)TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation., , , and . ECCV (1), volume 3951 of Lecture Notes in Computer Science, page 1-15. Springer, (2006)