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Rotation estimation of known rigid objects is important for robotic applications such as dexterous manipulation.
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Kehl, W., Milletari, F., Tombari, F., Ilic, S., Navab, N.: Deep learning of local rgb-d patches for 3d object detection and 6d pose estimation. In: ECCV (2016)
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Kehl, W., Manhardt, F., Tombari, F., Ilic, S., Navab, N.: SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again. In: ICCV (2017)
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Mahendran, S., Ali, H., Vidal, R.: 3d pose regression using convolutional neural networks. In: ICCV (2017)
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Michel, F., Kirillov, A., Brachmann, E., Krull, A., Gumhold, S., Savchynskyy, B., Rother, C.: Global hypothesis generation for 6d object pose estimation. In: CVPR (2017)
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Tejani, A., Kouskouridas, R., Doumanoglou, A., Tang, D., Kim, T.: Latent-class hough forests for 6 dof object pose estimation. PAMI 40
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