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D
Brachmann, E, Krull, A, Nowozin, S, Shotton, J, Michel, F, Gumhold, S and Rother, C (2017). DSAC - Differentiable RANSAC for camera localization. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua 2492–2500. http://arxiv.org/abs/1611.05705
O
Zheng, S, Prisacariu, V Adrian, Averkiou, M, Cheng, M Ming, Mitra, N J, Shotton, J, Torr, P H S and Rother, C (2015). Object proposals estimation in depth image using compact 3D shape manifolds. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9358 196–208
P
Krull, A, Brachmann, E, Nowozin, S, Michel, F, Shotton, J and Rother, C (2017). PoseAgent: Budget-constrained 6D object pose estimation via reinforcement learning. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua 2566–2574. http://arxiv.org/abs/1612.03779
T
Shotton, J, Winn, J, Rother, C and Criminisi, A (2009). TextonBoost for image understanding: Multi-class object recognition and segmentation by jointly modeling texture, layout, and context. International Journal of Computer Vision. 81 2–23. http://jamie.shotton.org/work/code.html
Shotton, J, Winn, J, Rother, C and Criminisi, A (2006). TextonBoost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3951 LNCS 1–15. http://research.microsoft.com/vision/cambridge/recognition/.