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Multi-label Object Categorization Using Histograms of Global Relations.

, , , , , and . 3DV, page 309-317. IEEE Computer Society, (2015)

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Learning Abstract Classes using Deep Learning., , and . BICT, page 524-528. ICST/ACM, (2015)Learning Movement Assessment Primitives for Force Interaction Skills., , and . CoRR, (2018)Proceedings of the 37th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM/AAPR), 2013, and . CoRR, (2013)It Gets Worse Before it Gets Better: Timing of Instructions in Close Human-Robot Collaboration., , , , , and . HRI (Companion), page 145-146. ACM, (2017)Visual task outcome verification using deep learning., , and . IROS, page 4821-4827. IEEE, (2017)Multiview feature distributions for object detection and continuous pose estimation., and . Comput. Vis. Image Underst., (2014)Combining active learning and reactive control for robot grasping., , , and . Robotics Auton. Syst., 58 (9): 1105-1116 (2010)Can computer vision problems benefit from structured hierarchical classification?, , and . Mach. Vis. Appl., 27 (8): 1299-1312 (2016)Unsupervised Learning of Visual Feature Hierarchies., and . MLDM, volume 3587 of Lecture Notes in Computer Science, page 243-252. Springer, (2005)Can Computer Vision Problems Benefit from Structured Hierarchical Classification?, , , and . CAIP (2), volume 9257 of Lecture Notes in Computer Science, page 403-414. Springer, (2015)