References
- Florian Chabot, Mohamed Chaouch, Jaonary Rabarisoa, Celine Teuliere and Thierry Chateau, "Deep MANTA: A coarse-to-fine many-task network for joint 2d and 3D vehicle analysis from monocular image," In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2040-2049, 2017.
- Wadim Kehl, Fabian Manhardt, Federico Tombari, Slobodan Ilic and Nassir Navab, "SSD-6D: Making rgb-based 3D detection and 6d pose estimation great again," In IEEE International Conference on Computer Vision, 2017.
- Jianxiong Xiao, Bryan Russell and Antonio Torralba, "Localizing 3D cuboids in single-view images," In Advances in neural information processing systems (NIPS), pp. 746-754, 2012.
- Xiaozhi Chen, Kaustav Kundu, Ziyu Zhang, Huimin Ma, Sanja Fidler and Raquel Urtasun, "Monocular 3D object detection for autonomous driving," In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2147-2156, 2016.
- S. Yang and S. Scherer, "Cubeslam: Monocular 3-d object slam," IEEE Transactions on Robotics, vol. 35, no. 4, pp. 925-938, 2019. https://doi.org/10.1109/tro.2019.2909168
- Raul Mur-Artal, J.M.M. Montiel and Juan D. Tardos, "ORB-SLAM: a versatile and accurate monocular SLAM system," IEEE Transactions on Robotics, 31(5):1147-1163, 2015. https://doi.org/10.1109/TRO.2015.2463671
- Jakob Engel, Vladlen Koltun and Daniel Cremers, "Direct sparse odometry," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017.
- Renato F. Salas-Moreno, Richard A. Newcombe, Hauke Strasdat, Paul H.J. Kelly and Andrew J. Davison, "SLAM++: Simultaneous localisation and mapping at the level of objects," In IEEE Conference on Computer Vision and Pattern Recognition, pp. 1352-1359, 2013.
- Dorian Galvez-Lopez, Marta Salas, Juan D. Tardos and J.M.M. Montiel, "Real-time monocular object SLAM," Robotics and Autonomous Systems, 75:435-449, 2016. https://doi.org/10.1016/j.robot.2015.08.009
- Nan Yang, Rui Wang, Jorg Stuckler and Daniel Cremers, "Leveraging deep depth prediction for monocular direct sparse odometry," In European Conference on Computer Vision, pp. 835-852. Springer, 2018.