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Multiview feature distributions for object detection and continuous pose estimation., and . Computer Vision and Image Understanding, (2014)Bottom-up learning of object categories, action effects and logical rules: From continuous manipulative exploration to symbolic planning., and . ICRA, page 2627-2633. IEEE, (2015)Feature Learning for Recognition with Bayesian Networks., and . ICPR, page 1017-1020. IEEE Computer Society, (2000)A Simple Ontology of Manipulation Actions Based on Hand-Object Relations., , , , , and . IEEE Trans. Autonomous Mental Development, 5 (2): 117-134 (2013)Closed-Loop Learning of Visual Control Policies., and . J. Artif. Intell. Res., (2007)A robust pushing skill for object delivery between obstacles., , and . CASE, page 1184-1189. IEEE, (2016)Combining active learning and reactive control for robot grasping., , , and . Robotics and Autonomous Systems, 58 (9): 1105-1116 (2010)Can computer vision problems benefit from structured hierarchical classification?, , and . Mach. Vis. Appl., 27 (8): 1299-1312 (2016)General Object Tip Detection and Pose Estimation for Robot Manipulation., , and . ICVS, volume 9163 of Lecture Notes in Computer Science, page 364-374. Springer, (2015)Unsupervised Learning of Visual Feature Hierarchies., and . MLDM, volume 3587 of Lecture Notes in Computer Science, page 243-252. Springer, (2005)