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Self-supervised pre-training for 3D vision has drawn increasing research interest in recent years.
2003
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2006
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Deng, J., Dong, W., Socher, R., Li, L., Kai Li, Li Fei-Fei: ImageNet: A large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition. pp. 248–255 (2009)
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Maturana, D., Scherer, S.: VoxNet: A 3d convolutional neural network for real-time object recognition. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). pp. 922–928 (2015)
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Song, S., Lichtenberg, S.P., Xiao, J.: SUN RGB-D: A RGB-D scene understanding benchmark suite. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 567–576 (June 2015)
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Wang, X., Gupta, A.: Unsupervised learning of visual representations using videos. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV) (December 2015)
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Wu, Z., Song, S., Khosla, A., Yu, F., Zhang, L., Tang, X., Xiao, J.: 3d shapenets: A deep representation for volumetric shapes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2015)
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He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 770–778 (June 2016)
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Noroozi, M., Favaro, P.: Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) Computer Vision – ECCV 2016. pp. 69–84. Springer International Publishing, Cham (2016)
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Song, S., Xiao, J.: Deep sliding shapes for amodal 3d object detection in RGB-D images. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 808–816 (June 2016)
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Zhang, R., Isola, P., Efros, A.A.: Colorful Image Colorization. In: Computer Vision – ECCV 2016. pp. 649–666. Lecture Notes in Computer Science, Cham (2016). https://doi.org/10.1007/978-3-319-46487-9_40
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Dai, A., Chang, A.X., Savva, M., Halber, M., Funkhouser, T., Nießner, M.: ScanNet: Richly-annotated 3d reconstructions of indoor scenes. In: Proc. Computer Vision and Pattern Recognition (CVPR), IEEE (2017)
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Park, J., Zhou, Q.Y., Koltun, V.: Colored point cloud registration revisited. In: ICCV (2017)
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Qi, C.R., Su, H., Mo, K., Guibas, L.J.: PointNet: Deep learning on point sets for 3d classification and segmentation. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 652–660 (July 2017)
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Qi, C.R., Yi, L., Su, H., Guibas, L.J.: PointNet++: Deep hierarchical feature learning on point sets in a metric space. In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. (eds.) Advances in Neural Information Processing Systems 30, pp. 5099–5108. Curran Associates, Inc. (2017)
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Zhang, R., Isola, P., Efros, A.A.: Split-brain autoencoders: Unsupervised learning by cross-channel prediction. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (July 2017)
2017
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Achlioptas, P., Diamanti, O., Mitliagkas, I., Guibas, L.: Learning representations and generative models for 3d point clouds. In: International Conference on Machine Learning (ICML) (2018)
2018
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Dai, A., Nießner, M.: 3DMV: Joint 3d-multi-view prediction for 3d semantic scene segmentation. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) Computer Vision – ECCV 2018. Springer International Publishing, Cham (2018)
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2018
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Graham, B., Engelcke, M., van der Maaten, L.: 3d semantic segmentation with submanifold sparse convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2018)
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Chaitanya, K., Erdil, E., Karani, N., Konukoglu, E.: Contrastive learning of global and local features for medical image segmentation with limited annotations. In: Neural Information Processing Systems (2020)
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Chen, J., Lei, B., Song, Q., Ying, H., Chen, D.Z., Wu, J.: A hierarchical graph network for 3d object detection on point clouds. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (June 2020)
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Fan, D.P., Zhai, Y., Borji, A., Yang, J., Shao, L.: BBS-Net: RGB-D salient object detection with a bifurcated backbone strategy network. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.M. (eds.) Computer Vision – ECCV 2020. pp. 275–292. Springer International Publishing, Cham (2020)
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Grill, J.B., Strub, F., Altché, F., Tallec, C., Richemond, P., Buchatskaya, E., Doersch, C., Avila Pires, B., Guo, Z., Gheshlaghi Azar, M., Piot, B., kavukcuoglu, k., Munos, R., Valko, M.: Bootstrap your own latent - a new approach to self-supervised learning. In: Advances in Neural Information Processing Systems. vol. 33, pp. 21271–21284 (2020)
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Li, Y., Bu, R., Sun, M., Wu, W., Di, X., Chen, B.: PointCNN: Convolution on x-transformed points. In: Bengio, S., Wallach, H., Larochelle, H., Grauman, K., Cesa-Bianchi, N., Garnett, R. (eds.) Advances in Neural Information Processing Systems. vol. 31, pp. 820–830. Curran Associates, Inc. (2018)
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Qi, C.R., Liu, W., Wu, C., Su, H., Guibas, L.J.: Frustum PointNets for 3d object detection from RGB-D data. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 918–927 (June 2018)
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Wang, S., Suo, S., Ma, W.C., Pokrovsky, A., Urtasun, R.: Deep parametric continuous convolutional neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2018)
2018
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Xu, D., Anguelov, D., Jain, A.: PointFusion: Deep sensor fusion for 3d bounding box estimation. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 244–253 (June 2018)
2018
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Zhou, Y., Tuzel, O.: VoxelNet: End-to-end learning for point cloud based 3d object detection. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 4490–4499 (June 2018)
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Bachman, P., Hjelm, R.D., Buchwalter, W.: Learning representations by maximizing mutual information across views. In: Neural Information Processing Systems (2019)
2019
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Choy, C., Gwak, J., Savarese, S.: 4d spatio-temporal convnets: Minkowski convolutional neural networks. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3075–3084 (June 2019)
2019
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2020
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He, K., Fan, H., Wu, Y., Xie, S., Girshick, R.: Momentum contrast for unsupervised visual representation learning. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (June 2020)
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Li, G., Liu, Z., Ye, L., Wang, Y., Ling, H.: Cross-modal weighting network for RGB-D salient object detection. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.M. (eds.) Computer Vision – ECCV 2020. pp. 665–681. Springer International Publishing, Cham (2020)
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Misra, I., Maaten, L.v.d.: Self-supervised learning of pretext-invariant representations. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (June 2020)
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Pinheiro, P.O., Almahairi, A., Benmalek, R.Y., Golemo, F., Courville, A.C.: Unsupervised learning of dense visual representations. In: Neural Information Processing Systems (2020)
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Qi, C.R., Chen, X., Litany, O., Guibas, L.J.: ImVoteNet: Boosting 3d object detection in point clouds with image votes. In: The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 4404–4413 (June 2020)
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Sanghi, A.: Info3d: Representation learning on 3d objects using mutual information maximization and contrastive learning. In: ECCV (2020)
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Shi, S., Guo, C., Jiang, L., Wang, Z., Shi, J., Wang, X., Li, H.: PV-RCNN: Point-voxel feature set abstraction for 3d object detection. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (June 2020)
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Xie, S., Gu, J., Guo, D., Qi, C.R., Guibas, L., Litany, O.: PointContrast: Unsupervised pre-training for 3d point cloud understanding. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.M. (eds.) Computer Vision – ECCV 2020. pp. 574–591. Springer International Publishing, Cham (2020)
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Xing, Y., Wang, J., Zeng, G.: Malleable 2.5d convolution: Learning receptive fields along the depth-axis for RGB-D scene parsing. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.M. (eds.) Computer Vision – ECCV 2020. pp. 555–571. Springer International Publishing, Cham (2020)
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Chen, X., He, K.: Exploring simple siamese representation learning. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 15750–15758 (June 2021)
2021
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Hou, J., Graham, B., Nießner, M., Xie, S.: Exploring data-efficient 3d scene understanding with contrastive scene contexts. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 15587–15597 (2021)
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Li, L., Heizmann, M.: 2.5D-VoteNet: Depth map based 3d object detection for real-time applications. In: Britisch Machine Vision Conference (BMVC) (2021)
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2021
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Liu, Z., Qi, X., Fu, C.W.: 3d-to-2d distillation for indoor scene parsing. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 4464–4474 (June 2021)
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Wang, X., Zhang, R., Shen, C., Kong, T., Li, L.: Dense contrastive learning for self-supervised visual pre-training. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3024–3033 (June 2021)
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