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6D object pose estimation is a fundamental problem in computer vision.
Spelke, E.S.: Principles of object perception. Cognitive science 14
1990
Earlier work this paper cites.
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing (TIP) 13
2004
Earlier work this paper cites.
2004
Earlier work this paper cites.
Hinterstoisser, S., Lepetit, V., Ilic, S., Holzer, S., Bradski, G., Konolige, K., Navab, N.: Model based training, detection and pose estimation of texture-less 3d objects in heavily cluttered scenes. In: Asian Conference on Computer Vision (ACCV). pp. 548–562 (2012)
2012
Earlier work this paper cites.
Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems (NeurIPS). pp. 1097–1105 (2012)
2012
Earlier work this paper cites.
Hinterstoisser, S., Lepetit, V., Ilic, S., Holzer, S., Bradski, G., Konolige, K., Navab, N.: Model based training, detection and pose estimation of texture-less 3d objects in heavily cluttered scenes. In: Asian Conference on Computer Vision (ACCV). pp. 548–562 (2012)
2012
Earlier work this paper cites.
Brachmann, E., Krull, A., Michel, F., Gumhold, S., Shotton, J., Rother, C.: Learning 6D object pose estimation using 3D object coordinates. In: European Conference on Computer Vision (ECCV). pp. 536–551 (2014)
2014
Earlier work this paper cites.
Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: Microsoft coco: Common objects in context. In: European Conference on Computer Vision (ECCV). pp. 740–755 (2014)
2014
Earlier work this paper cites.
Loper, M.M., Black, M.J.: OpenDR: An approximate differentiable renderer. In: European Conference on Computer Vision (ECCV). vol. 8695, pp. 154–169 (2014)
2014
Earlier work this paper cites.
Brachmann, E., Krull, A., Michel, F., Gumhold, S., Shotton, J., Rother, C.: Learning 6D object pose estimation using 3D object coordinates. In: European Conference on Computer Vision (ECCV). pp. 536–551 (2014)
2014
Earlier work this paper cites.
Marschner, S., Shirley, P.: Fundamentals of computer graphics. CRC Press (2015)
2015
Earlier work this paper cites.
Su, H., Qi, C.R., Li, Y., Guibas, L.J.: Render for cnn: Viewpoint estimation in images using cnns trained with rendered 3d model views. In: IEEE International Conference on Computer Vision (ICCV). pp. 2686–2694 (2015)
2015
Earlier work this paper cites.
Wohlhart, P., Lepetit, V.: Learning descriptors for object recognition and 3d pose estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3109–3118 (2015)
2015
Earlier work this paper cites.
Wohlhart, P., Lepetit, V.: Learning descriptors for object recognition and 3d pose estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3109–3118 (2015)
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
Brachmann, E., Michel, F., Krull, A., Ying Yang, M., Gumhold, S., Rother, C.: Uncertainty-driven 6D pose estimation of objects and scenes from a single RGB image. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3364–3372 (2016)
2016
Earlier work this paper cites.
Hodaň, T., Matas, J., Obdržálek, Š.: On evaluation of 6d object pose estimation. European Conference on Computer Vision Workshops (ECCVW) pp. 606–619 (2016)
2016
Earlier work this paper cites.
Johnson, J., Alahi, A., Fei-Fei, L.: Perceptual losses for real-time style transfer and super-resolution. In: European Conference on Computer Vision (ECCV). pp. 694–711 (2016)
2016
Earlier work this paper cites.
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: European Conference on Computer Vision (ECCV). pp. 205–220 (2016)
2016
Earlier work this paper cites.
Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y., Berg, A.C.: SSD: Single shot multibox detector. In: European Conference on Computer Vision (ECCV). pp. 21–37 (2016)
2016
Earlier work this paper cites.
Richter, S.R., Vineet, V., Roth, S., Koltun, V.: Playing for data: Ground truth from computer games. In: European Conference on Computer Vision (ECCV). pp. 102–118 (2016)
2016
Earlier work this paper cites.
Zhao, H., Gallo, O., Frosio, I., Kautz, J.: Loss functions for image restoration with neural networks. IEEE Transactions on Computational Imaging 3
2016
Earlier work this paper cites.
Bousmalis, K., Silberman, N., Dohan, D., Erhan, D., Krishnan, D.: Unsupervised pixel-level domain adaptation with generative adversarial networks. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3722–3731 (2017)
2017
Earlier work this paper cites.
Dwibedi, D., Misra, I., Hebert, M.: Cut, paste and learn: Surprisingly easy synthesis for instance detection. In: IEEE International Conference on Computer Vision (ICCV). pp. 1301–1310 (2017)
2017
Earlier work this paper cites.
Godard, C., Mac Aodha, O., Brostow, G.J.: Unsupervised monocular depth estimation with left-right consistency. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 270–279 (2017)
2017
Earlier work this paper cites.
Hodan, T., Haluza, P., Obdržálek, Š., Matas, J., Lourakis, M., Zabulis, X.: T-less: An rgb-d dataset for 6d pose estimation of texture-less objects. In: IEEE Winter Conference on Applications of Computer Vision (WACV). pp. 880–888 (2017)
2017
Earlier work this paper cites.
Kehl, W., Manhardt, F., Tombari, F., Ilic, S., Navab, N.: Ssd-6d: Making rgb-based 3d detection and 6d pose estimation great again. In: IEEE International Conference on Computer Vision (ICCV). pp. 1521–1529 (2017)
2017
Earlier work this paper cites.
Lin, T.Y., Dollár, P., Girshick, R., He, K., Hariharan, B., Belongie, S.: Feature pyramid networks for object detection. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 2117–2125 (2017)
2017
Earlier work this paper cites.
Lin, T.Y., Goyal, P., Girshick, R., He, K., Dollar, P.: Focal loss for dense object detection. In: IEEE International Conference on Computer Vision (ICCV) (2017)
2017
Cited alongside, same era.
Rad, M., Lepetit, V.: BB8: A scalable, accurate, robust to partial occlusion method for predicting the 3D poses of challenging objects without using depth. In: IEEE International Conference on Computer Vision (ICCV). pp. 3828–3836 (2017)
2017
Cited alongside, same era.
Tung, H.Y., Tung, H.W., Yumer, E., Fragkiadaki, K.: Self-supervised learning of motion capture. In: NeurIPS. pp. 5236–5246 (2017)
2017
Cited alongside, same era.
Ilya Loshchilov, F.H.: SGDR: stochastic gradient descent with warm restarts. In: International Conference on Learning Representations (ICLR) (2017)
2017
Cited alongside, same era.
Hodaň, T., Vineet, V., Gal, R., Shalev, E., Hanzelka, J., Connell, T., Urbina, P., Sinha, S., Guenter, B.: Photorealistic image synthesis for object instance detection. IEEE International Conference on Image Processing (ICIP) (2019)
2019
Later among the works it cites.
Hu, Y., Hugonot, J., Fua, P., Salzmann, M.: Segmentation-driven 6d object pose estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3385–3394 (2019)
2019
Later among the works it cites.
Jiang, P.T., Hou, Q., Cao, Y., Cheng, M.M., Wei, Y., Xiong, H.K.: Integral object mining via online attention accumulation. In: IEEE International Conference on Computer Vision (ICCV). pp. 2070–2079 (2019)
2019
Later among the works it cites.
Kaskman, R., Zakharov, S., Shugurov, I., Ilic, S.: HomebrewedDB: RGB-D dataset for 6d pose estimation of 3d objects. In: IEEE International Conference on Computer Vision Workshops (ICCVW) (2019)
2019
Later among the works it cites.
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2017
Cited alongside, same era.
Hodan, T., Michel, F., Brachmann, E., Kehl, W., GlentBuch, A., Kraft, D., Drost, B., Vidal, J., Ihrke, S., Zabulis, X., et al.: BOP: Benchmark for 6d object pose estimation. In: European Conference on Computer Vision (ECCV). pp. 19–34 (2018)
2018
Cited alongside, same era.
Kanazawa, A., Tulsiani, S., Efros, A.A., Malik, J.: Learning category-specific mesh reconstruction from image collections. In: European Conference on Computer Vision (ECCV). pp. 371–386 (2018)
2018
Cited alongside, same era.
Kato, H., Ushiku, Y., Harada, T.: Neural 3d mesh renderer. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3907–3916 (2018)
2018
Cited alongside, same era.
Lee, H.Y., Tseng, H.Y., Huang, J.B., Singh, M., Yang, M.H.: Diverse image-to-image translation via disentangled representations. In: European Conference on Computer Vision (ECCV). pp. 35–51 (2018)
2018
Cited alongside, same era.
Liu, R., Lehman, J., Molino, P., Such, F.P., Frank, E., Sergeev, A., Yosinski, J.: An intriguing failing of convolutional neural networks and the coordconv solution. In: Advances in Neural Information Processing Systems (NeurIPS). pp. 9605–9616 (2018)
2018
Cited alongside, same era.
Manhardt, F., Kehl, W., Navab, N., Tombari, F.: Deep model-based 6d pose refinement in rgb. In: European Conference on Computer Vision (ECCV). pp. 800–815 (2018)
2018
Cited alongside, same era.
Omran, M., Lassner, C., Pons-Moll, G., Gehler, P., Schiele, B.: Neural body fitting: Unifying deep learning and model based human pose and shape estimation. In: 3DV. pp. 484–494 (2018)
2018
Cited alongside, same era.
Kocabas, M., Karagoz, S., Akbas, E.: Self-supervised learning of 3d human pose using multi-view geometry. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1077–1086 (2019)
2019
Later among the works it cites.
Kolesnikov, A., Zhai, X., Beyer, L.: Revisiting self-supervised visual representation learning. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1920–1929 (2019)
2019
Later among the works it cites.
Li, Y., Wang, G., Ji, X., Xiang, Y., Fox, D.: DeepIM: Deep iterative matching for 6d pose estimation. International Journal of Computer Vision (IJCV) pp. 1–22 (2019)
2019
Later among the works it cites.
Li, Z., Wang, G., Ji, X.: CDPN: Coordinates-Based Disentangled Pose Network for Real-Time RGB-Based 6-DoF Object Pose Estimation. In: IEEE International Conference on Computer Vision (ICCV). pp. 7678–7687 (2019)
2019
Later among the works it cites.
Liu, S., Li, T., Chen, W., Li, H.: Soft rasterizer: A differentiable renderer for image-based 3d reasoning. IEEE International Conference on Computer Vision (ICCV) pp. 7708–7717 (2019)
2019
Later among the works it cites.
Manhardt, F., Arroyo, D., Rupprecht, C., Busam, B., Birdal, T., Navab, N., Tombari, F.: Explaining the ambiguity of object detection and 6d pose from visual data. In: IEEE International Conference on Computer Vision (ICCV). pp. 6841–6850 (2019)
2019
Later among the works it cites.
Manhardt, F., Kehl, W., Gaidon, A.: ROI-10D: Monocular lifting of 2d detection to 6d pose and metric shape. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 2069–2078 (2019)
2019
Later among the works it cites.
Park, K., Patten, T., Vincze, M.: Pix2pose: Pixel-wise coordinate regression of objects for 6d pose estimation. In: IEEE International Conference on Computer Vision (ICCV). pp. 7668–7677 (2019)
2019
Later among the works it cites.
Peng, S., Liu, Y., Huang, Q., Zhou, X., Bao, H.: Pvnet: Pixel-wise voting network for 6dof pose estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 4561–4570 (2019)
2019
Later among the works it cites.
Pillai, S., Ambruş, R., Gaidon, A.: Superdepth: Self-supervised, super-resolved monocular depth estimation. In: IEEE International Conference on Robotics and Automation (ICRA). pp. 9250–9256 (2019)
2019
Later among the works it cites.
Rezatofighi, H., Tsoi, N., Gwak, J., Sadeghian, A., Reid, I., Savarese, S.: Generalized intersection over union: A metric and a loss for bounding box regression. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 658–666 (2019)
2019
Later among the works it cites.
Tian, Z., Shen, C., Chen, H., He, T.: FCOS: Fully convolutional one-stage object detection. In: IEEE International Conference on Computer Vision (ICCV). pp. 9627–9636 (2019)
2019
Later among the works it cites.
Zakharov, S., Kehl, W., Ilic, S.: Deceptionnet: Network-driven domain randomization. In: IEEE International Conference on Computer Vision (ICCV). pp. 532–541 (2019)
2019
Later among the works it cites.
Zakharov, S., Shugurov, I., Ilic, S.: Dpod: 6d pose object detector and refiner. In: IEEE International Conference on Computer Vision (ICCV). pp. 1941–1950 (2019)
2019
Later among the works it cites.
Zuffi, S., Kanazawa, A., Berger-Wolf, T., Black, M.J.: Three-d safari: Learning to estimate zebra pose, shape, and texture from images “in the wild”. In: IEEE International Conference on Computer Vision (ICCV). pp. 5359–5368 (2019)
2019
Later among the works it cites.
Kaskman, R., Zakharov, S., Shugurov, I., Ilic, S.: HomebrewedDB: RGB-D dataset for 6d pose estimation of 3d objects. In: IEEE International Conference on Computer Vision Workshops (ICCVW) (2019)
2019
Later among the works it cites.
Manhardt, F., Kehl, W., Gaidon, A.: ROI-10D: Monocular lifting of 2d detection to 6d pose and metric shape. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 2069–2078 (2019)
2019
Later among the works it cites.
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et al.: Pytorch: An imperative style, high-performance deep learning library. In: NeurIPS. pp. 8026–8037 (2019)
2019
Later among the works it cites.
Zakharov, S., Shugurov, I., Ilic, S.: Dpod: 6d pose object detector and refiner. In: IEEE International Conference on Computer Vision (ICCV). pp. 1941–1950 (2019)
2019
Later among the works it cites.
Zhang, M., Lucas, J., Ba, J., Hinton, G.E.: Lookahead optimizer: k steps forward, 1 step back. In: Advances in Neural Information Processing Systems (NeurIPS). pp. 9593–9604 (2019)
2019
Later among the works it cites.
Deng, X., Xiang, Y., Mousavian, A., Eppner, C., Bretl, T., Fox, D.: Self-supervised 6d object pose estimation for robot manipulation. In: IEEE International Conference on Robotics and Automation (ICRA) (2020)
2020
Closest in time.
Guizilini, V., Ambrus, R., Pillai, S., Raventos, A., Gaidon, A.: 3d packing for self-supervised monocular depth estimation. In: CVPR (June 2020)
2020
Closest in time.
Liu, L., Jiang, H., He, P., Chen, W., Liu, X., Gao, J., Han, J.: On the variance of the adaptive learning rate and beyond. In: International Conference on Learning Representations (ICLR) (April 2020)
2020
Closest in time.