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Scene understanding from images is a challenging problem encountered in autonomous driving.
S. Dambreville, Y. Rathi, and A. Tannenbaum, “A framework for image segmentation using shape models and kernel space shape priors,” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) , vol. 30, no. 8, pp. 1385–1399, 2008
2008
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P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan, “Object detection with discriminatively trained part-based models,” IEEE transactions on pattern analysis and machine intelligence , vol. 32, no. 9, pp. 1627–1645, 2009
2009
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A. Geiger, M. Roser, and R. Urtasun, “Efficient large-scale stereo matching,” in Asian conference on computer vision . Springer, 2010, pp. 25–38
2010
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R. Sandhu, S. Dambreville, A. Yezzi, and A. Tannenbaum, “A nonrigid kernel-based framework for 2D-3D pose estimation and 2D image segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 33, no. 6, pp. 1098–1115, 2011
2011
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R. Sandhu, S. Dambreville, A. Yezzi, and A. Tannenbaum, “A nonrigid kernel-based framework for 2D-3D pose estimation and 2D image segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) , vol. 33, no. 6, pp. 1098–1115, 2011
2011
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V. A. Prisacariu and I. Reid, “Nonlinear shape manifolds as shape priors in level set segmentation and tracking,” in Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on . IEEE, 2011, pp. 2185–2192
2011
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2011
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V. A. Prisacariu, A. V. Segal, and I. Reid, “Simultaneous monocular 2D segmentation, 3D pose recovery and 3D reconstruction,” in Asian Conference on Computer Vision . Springer, 2012, pp. 593–606
2012
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A. Geiger, P. Lenz, and R. Urtasun, “Are we ready for autonomous driving? the KITTI vision benchmark suite,” in Conference on Computer Vision and Pattern Recognition (CVPR) , 2012
2012
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S. Satkin and M. Hebert, “3DNN: Viewpoint invariant 3D geometry matching for scene understanding,” in IEEE International Conference on Computer Vision, (ICCV) , 2013, pp. 1873–1880
2013
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R. F. Salas-Moreno, R. A. Newcombe, H. Strasdat, P. H. J. Kelly, and A. J. Davison, “SLAM++: Simultaneous Localisation and Mapping at the Level of Objects,” in 2013 IEEE Conference on Computer Vision and Pattern Recognition , 2013, pp. 1352–1359
2013
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V. A. Prisacariu, A. V. Segal, and I. Reid, “Simultaneous monocular 2D segmentation, 3D pose recovery and 3D reconstruction,” in Proc. of the Asian Conf. on Computer Vision (ACCV) , 2013
2013
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A. Dame, V. A. Prisacariu, C. Y. Ren, and I. D. Reid, “Dense reconstruction using 3D object shape priors,” in Proc. of the IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR) , 2013
2013
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J. Engel, J. Sturm, and D. Cremers, “Semi-dense visual odometry for a monocular camera,” in Computer Vision (ICCV), 2013 IEEE International Conference on . IEEE, 2013, pp. 1449–1456
2013
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S. Song and J. Xiao, “Sliding shapes for 3d object detection in depth images,” in European Conference on Computer Vision (ECCV) , 2014, pp. 634–651
2014
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J. Engel, T. Schöps, and D. Cremers, “LSD-SLAM: Large-scale direct monocular SLAM,” in European Conference on Computer Vision (ECCV) . Springer, 2014, pp. 834–849
2014
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S. Ren, K. He, R. Girshick, and J. Sun, “Faster R-CNN: Towards real-time object detection with region proposal networks,” in Advances in Neural Information Processing Systems (NIPS) , 2015, pp. 91–99
2015
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X. Chen, K. Kundu, Y. Zhu, A. Berneshawi, H. Ma, S. Fidler, and R. Urtasun, “3d object proposals for accurate object class detection,” in NIPS , 2015
2015
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A. Geiger and C. Wang, “Joint 3D Object and Layout Inference from a single RGB-D Image,” in German Conference on Pattern Recognition (GCPR) , ser. Lecture Notes in Computer Science, vol. 9358. Springer International Publishing, 2015, pp. 183–195
2015
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L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille, “DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,” IEEE transactions on pattern analysis and machine intelligence , vol. 40, no. 4, pp. 834–848, 2017
2017
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K. He, G. Gkioxari, P. Dollár, and R. Girshick, “Mask R-CNN,” in Computer Vision (ICCV), 2017 IEEE International Conference on . IEEE, 2017, pp. 2980–2988
2017
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A. Mousavian, D. Anguelov, J. Flynn, and J. Kosecka, “3D bounding box estimation using deep learning and geometry,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 7074–7082
2017
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R. Wang, M. Schwörer, and D. Cremers, “Stereo DSO: Large-scale direct sparse visual odometry with stereo cameras,” in International Conference on Computer Vision (ICCV), Venice, Italy , 2017
2017
Later among the works it cites.
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S. Zheng, V. A. Prisacariu, M. Averkiou, M.-M. Cheng, N. J. Mitra, J. Shotton, P. H. Torr, and C. Rother, “Object proposals estimation in depth image using compact 3d shape manifolds,” in German Conference on Pattern Recognition (GCPR) . Springer, 2015, pp. 196–208
2015
Cited alongside, same era.
M. Menze and A. Geiger, “Object scene flow for autonomous vehicles,” in Conference on Computer Vision and Pattern Recognition (CVPR) , 2015
2015
Cited alongside, same era.
C. Zhou, F. Güney, Y. Wang, and A. Geiger, “Exploiting object similarity in 3D reconstruction,” in Proc. of the IEEE Int. Conf. on Computer Vision (ICCV) , 2015
2015
Cited alongside, same era.
F. Engelmann, J. Stückler, and B. Leibe, “Joint object pose estimation and shape reconstruction in urban street scenes using 3D shape priors,” in German Conference on Pattern Recognition (GCPR) . Springer, 2016, pp. 219–230
2016
Cited alongside, same era.
J. Dai, Y. Li, K. He, and J. Sun, “R-FCN: Object detection via region-based fully convolutional networks,” in Advances in neural information processing systems , 2016, pp. 379–387
2016
Cited alongside, same era.
X. Chen, K. Kundu, Z. Zhang, H. Ma, S. Fidler, and R. Urtasun, “Monocular 3D object detection for autonomous driving,” in IEEE CVPR , 2016
2016
Cited alongside, same era.
R. Ortiz-Cayon, A. Djelouah, F. Massa, M. Aubry, and G. Drettakis, “Automatic 3D Car Model Alignment for Mixed Image-Based Rendering,” in International Conference on 3D Vision (3DV) , 2016
2016
Cited alongside, same era.
——, “SAMP: Shape and motion priors for 4D vehicle reconstruction,” in Applications of Computer Vision (WACV), 2017 IEEE Winter Conference on . IEEE, 2017, pp. 400–408
2017
Cited alongside, same era.
B. Xu and Z. Chen, “Multi-level fusion based 3D object detection from monocular images,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 2345–2353
2018
Later among the works it cites.
A. Kundu, Y. Li, and J. M. Rehg, “3D-RCNN: Instance-level 3D object reconstruction via render-and-compare,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 3559–3568
2018
Later among the works it cites.
J. Engel, V. Koltun, and D. Cremers, “Direct sparse odometry,” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) , vol. 40, no. 3, pp. 611–625, 2018
2018
Later among the works it cites.
N. Yang, R. Wang, J. Stuckler, and D. Cremers, “Deep virtual stereo odometry: Leveraging deep depth prediction for monocular direct sparse odometry,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 817–833
2018
Later among the works it cites.
X. Gao, R. Wang, N. Demmel, and D. Cremers, “LDSO: Direct sparse odometry with loop closure,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2018, pp. 2198–2204
2018
Later among the works it cites.
R. Zhu, C. Wang, C.-H. Lin, Z. Wang, and S. Lucey, “Object-centric photometric bundle adjustment with deep shape prior,” in 2018 IEEE Winter Conference on Applications of Computer Vision (WACV) . IEEE, 2018, pp. 894–902
2018
Later among the works it cites.
J.-R. Chang and Y.-S. Chen, “Pyramid stereo matching network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 5410–5418
2018
Later among the works it cites.
A. Kirillov, K. He, R. Girshick, C. Rother, and P. Dollár, “Panoptic segmentation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 9404–9413
2019
Closest in time.
P. Li, X. Chen, and S. Shen, “Stereo R-CNN based 3D object detection for autonomous driving,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019
2019
Closest in time.
Y. Wang, W.-L. Chao, D. Garg, B. Hariharan, M. Campbell, and K. Q. Weinberger, “Pseudo-LiDAR from visual depth estimation: Bridging the gap in 3D object detection for autonomous driving,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 8445–8453
2019
Closest in time.