Fetching the paper…
Reading the bibliography…
In this paper, we propose a transformer-based procedure for the efficient registration of non-rigid 3D point clouds.
Besl, P.J., McKay, N.D.: A method for registration of 3-d shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14
1992
Earlier work this paper cites.
Allen, B., Curless, B., Popović, Z.: The space of human body shapes: reconstruction and parameterization from range scans. ACM transactions on graphics (TOG) 22
2003
Earlier work this paper cites.
Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., Davis, J.: Scape: shape completion and animation of people. In: ACM SIGGRAPH 2005 Papers, pp. 408–416 (2005)
2005
Earlier work this paper cites.
Amberg, B., Romdhani, S., Vetter, T.: Optimal step nonrigid icp algorithms for surface registration. In: 2007 IEEE conference on computer vision and pattern recognition. pp. 1–8. IEEE (2007)
2007
Earlier work this paper cites.
Li, H., Sumner, R.W., Pauly, M.: Global correspondence optimization for non-rigid registration of depth scans. Computer graphics forum 27
2008
Earlier work this paper cites.
Jian, B., Vemuri, B.C.: Robust point set registration using gaussian mixture models. IEEE transactions on pattern analysis and machine intelligence 33
2010
Earlier work this paper cites.
Myronenko, A., Song, X.: Point set registration: Coherent point drift. IEEE transactions on pattern analysis and machine intelligence 32
2010
Earlier work this paper cites.
Kim, V.G., Lipman, Y., Funkhouser, T.: Blended intrinsic maps. ACM Transactions on Graphics (TOG) 30
2011
Earlier work this paper cites.
Van Kaick, O., Zhang, H., Hamarneh, G., Cohen-Or, D.: A survey on shape correspondence. Computer graphics forum 30
2011
Earlier work this paper cites.
Hirshberg, D.A., Loper, M., Rachlin, E., Black, M.J.: Coregistration: Simultaneous alignment and modeling of articulated 3d shape. In: European conference on computer vision. pp. 242–255. Springer (2012)
2012
Earlier work this paper cites.
Ovsjanikov, M., Ben-Chen, M., Solomon, J., Butscher, A., Guibas, L.: Functional maps: a flexible representation of maps between shapes. ACM Transactions on Graphics (TOG) 31
2012
Earlier work this paper cites.
Bogo, F., Romero, J., Loper, M., Black, M.J.: FAUST: Dataset and evaluation for 3D mesh registration. In: Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR). IEEE, Piscataway, NJ, USA (Jun 2014)
2014
Earlier work this paper cites.
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., Black, M.J.: Smpl: A skinned multi-person linear model. ACM transactions on graphics (TOG) 34
2015
Earlier work this paper cites.
Zuffi, S., Black, M.J.: The stitched puppet: A graphical model of 3d human shape and pose. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 3537–3546 (2015)
2015
Earlier work this paper cites.
Ezuz, D., Ben-Chen, M.: Deblurring and denoising of maps between shapes. Computer Graphics Forum 36
2017
Earlier work this paper cites.
Litany, O., Remez, T., Rodolà, E., Bronstein, A., Bronstein, M.: Deep functional maps: Structured prediction for dense shape correspondence. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 5659–5667 (2017)
2017
Earlier work this paper cites.
Nogneng, D., Ovsjanikov, M.: Informative descriptor preservation via commutativity for shape matching. Computer Graphics Forum 36
2017
Earlier work this paper cites.
Ovsjanikov, M., Corman, E., Bronstein, M., Rodolà, E., Ben-Chen, M., Guibas, L., Chazal, F., Bronstein, A.: Computing and processing correspondences with functional maps. In: SIGGRAPH 2017 Courses (2017)
2017
Cited alongside, same era.
Qi, C.R., Su, H., Mo, K., Guibas, L.J.: Pointnet: Deep learning on point sets for 3d classification and segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 652–660 (2017)
2017
Cited alongside, same era.
Varol, G., Romero, J., Martin, X., Mahmood, N., Black, M.J., Laptev, I., Schmid, C.: Learning from synthetic humans. In: CVPR (2017)
2017
Cited alongside, same era.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention is all you need. In: Proc. NIPS (2017)
2017
Cited alongside, same era.
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., Houlsby, N.: An image is worth 16x16 words: Transformers for image recognition at scale (2020)
2020
Later among the works it cites.
Eisenberger, M., Lahner, Z., Cremers, D.: Smooth shells: Multi-scale shape registration with functional maps. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 12265–12274 (2020)
2020
Later among the works it cites.
2020
Later among the works it cites.
Engel, N., Belagiannis, V., Dietmayer, K.: Point transformer (2020)
2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Zuffi, S., Kanazawa, A., Jacobs, D.W., Black, M.J.: 3d menagerie: Modeling the 3d shape and pose of animals. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 6365–6373 (2017)
2017
Cited alongside, same era.
Groueix, T., Fisher, M., Kim, V.G., Russell, B.C., Aubry, M.: 3d-coded: 3d correspondences by deep deformation. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 230–246 (2018)
2018
Cited alongside, same era.
Radford, A., Narasimhan, K., Salimans, T., Sutskever, I.: Improving language understanding by generative pre-training (2018)
2018
Cited alongside, same era.
Ranjan, A., Bolkart, T., Sanyal, S., Black, M.J.: Generating 3D faces using convolutional mesh autoencoders. In: European Conference on Computer Vision (ECCV). pp. 725–741 (2018)
2018
Cited alongside, same era.
2019
Cited alongside, same era.
Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: Pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). pp. 4171–4186. Association for Computational Linguistics, Minneapolis, Minnesota (Jun 2019). https://doi.org/10.18653/v1/N19-1423, https://www.aclweb.org/anthology/N19-1423
2019
Cited alongside, same era.
Marin, R., Melzi, S., Rodolà, E., Castellani, U.: High-resolution augmentation for automatic template-based matching of human models. In: 2019 International Conference on 3D Vision (3DV). pp. 230–239. IEEE (2019)
2019
Cited alongside, same era.
Melzi, S., Marin, R., Rodolà, E., Castellani, U., Ren, J., Poulenard, A., Wonka, P., Ovsjanikov, M.: Matching Humans with Different Connectivity. In: Biasotti, S., Lavoué, G., Veltkamp, R. (eds.) Eurographics Workshop on 3D Object Retrieval. The Eurographics Association (2019)
2019
Cited alongside, same era.
Hirose, O.: A bayesian formulation of coherent point drift. IEEE Transactions on Pattern Analysis and Machine Intelligence pp. 1–1 (2020). https://doi.org/10.1109/TPAMI.2020.2971687
2020
Later among the works it cites.
Huang, X., Mei, G., Zhang, J.: Feature-metric registration: A fast semi-supervised approach for robust point cloud registration without correspondences. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (June 2020)
2020
Later among the works it cites.
Marin, R., Melzi, S., Rodolà, E., Castellani, U.: Farm: Functional automatic registration method for 3d human bodies. Computer Graphics Forum 39
2020
Later among the works it cites.
Marin, R., Rakotosaona, M.J., Melzi, S., Ovsjanikov, M.: Correspondence learning via linearly-invariant embedding. In: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M.F., Lin, H. (eds.) Advances in Neural Information Processing Systems. vol. 33, pp. 1608–1620. Curran Associates, Inc. (2020)
2020
Later among the works it cites.
Melzi, S., Marin, R., Musoni, P., Bardon, F., Tarini, M., Castellani, U.: Intrinsic/extrinsic embedding for functional remeshing of 3d shapes. Computers & Graphics 88
2020
Later among the works it cites.
Pais, G.D., Ramalingam, S., Govindu, V.M., Nascimento, J.C., Chellappa, R., Miraldo, P.: 3dregnet: A deep neural network for 3d point registration. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 7193–7203 (2020)
2020
Later among the works it cites.
Ren, J., Melzi, S., Ovsjanikov, M., Wonka, P.: Maptree: Recovering multiple solutions in the space of maps. ACM Trans. Graph. 39
2020
Later among the works it cites.
Sahillioğlu, Y.: Recent advances in shape correspondence. The Visual Computer 36
2020
Later among the works it cites.
2020
Later among the works it cites.
Xu, H., Bazavan, E.G., Zanfir, A., Freeman, W.T., Sukthankar, R., Sminchisescu, C.: Ghum & ghuml: Generative 3d human shape and articulated pose models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 6184–6193 (2020)
2020
Later among the works it cites.
Zhao, H., Jiang, L., Jia, J., Torr, P., Koltun, V.: Point transformer (2020)
2020
Later among the works it cites.
Scan the world project. https://www.myminifactory.com/scantheworld , [Online; accessed 04-June-2021]
2021
Closest in time.
Charlier, B., Feydy, J., Glaunès, J.A., Collin, F.D., Durif, G.: Kernel operations on the gpu, with autodiff, without memory overflows. Journal of Machine Learning Research 22
2021
Closest in time.
Guo, M.H., Cai, J.X., Liu, Z.N., Mu, T.J., Martin, R.R., Hu, S.M.: Pct: Point cloud transformer. Computational Visual Media pp. 187–99 (June 2021). https://doi.org/10.1007/s41095-021-0229-5
2021
Closest in time.
Jaegle, A., Gimeno, F., Brock, A., Zisserman, A., Vinyals, O., Carreira, J.: Perceiver: General perception with iterative attention (2021)
2021
Closest in time.