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We present RangeUDF, a new implicit representation based framework to recover the geometry and semantics of continuous 3D scene surfaces from point clouds.
Carr, J.C., Beatson, R.K., Cherrie, J.B., Mitchell, T.J., Fright, W.R., McCallum, B.C., Evans, T.R.: Reconstruction andrepresentation of 3D objects with radial basis functions. SIGGRAPH (2001)
2001
Earlier work this paper cites.
Guennebaud, G., Gross, M.: Algebraic point set surfaces. ACM Transactions on Graphics (2007)
2007
Earlier work this paper cites.
Kazhdan, M., Hoppe, H.: Screened Poisson Surface Reconstruction. ACM ToG 32
2013
Earlier work this paper cites.
Chang, A.X., Funkhouser, T., Guibas, L., Hanrahan, P., Huang, Q., Li, Z., Savarese, S., Savva, M., Song, S., Su, H., Xiao, J., Yi, L., Yu, F.: ShapeNet: An Information-Rich 3D Model Repository. arXiv (2015)
2015
Earlier work this paper cites.
Mur-Artal, R., Montiel, J.M.M., Tardos, J.D.: ORB-SLAM: a versatile and accurate monocular SLAM system. IEEE Trans on Robotics 31
2015
Earlier work this paper cites.
Cadena, C., Carlone, L., Carrillo, H., Latif, Y., Scaramuzza, D., Neira, J., Reid, I.D., Leonard, J.J.: Past, Present, and Future of Simultaneous Localization and Mapping: Towards the Robust-Perception Age. IEEE Transactions on Robotics 32
2016
Earlier work this paper cites.
Choy, C.B., Xu, D., Gwak, J., Chen, K., Savarese, S.: 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction. ECCV pp. 628–644 (2016)
2016
Earlier work this paper cites.
Hua, B.S., Pham, Q.H., Nguyen, D.T., Tran, M.K., Yu, L.F., Yeung, S.K.: SceneNN: A Scene Meshes Dataset with Annotations. 3DV (2016)
2016
Earlier work this paper cites.
Schonberger, J.L., Frahm, J.M.: Structure-from-Motion Revisited. CVPR (2016)
2016
Earlier work this paper cites.
Armeni, I., Sax, S., Zamir, A.R., Savarese, S.: Joint 2D-3D-Semantic Data for Indoor Scene Understanding. arXiv (2017)
2017
Earlier work this paper cites.
Berger, M., Tagliasacchi, A., Seversky, L.M., Alliez, P., Guennebaud, G., Levin, J.A., Sharf, A., Silva, C.T.: A Survey of Surface Reconstruction from Point Clouds. CFG (2017)
2017
Earlier work this paper cites.
Dai, A., Chang, A.X., Savva, M., Halber, M., Funkhouser, T., Nießner, M.: ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes. CVPR (2017)
2017
Earlier work this paper cites.
Fan, H., Su, H., Guibas, L.: A Point Set Generation Network for 3D Object Reconstruction from a Single Image. CVPR pp. 605–613 (2017)
2017
Earlier work this paper cites.
Ozyesil, O., Voroninski, V., Basri, R., Singer, A.: A Survey of Structure from Motion. Acta Numerica (2017)
2017
Earlier work this paper cites.
Qi, C.R., Su, H., Mo, K., Guibas, L.J.: PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. CVPR (2017)
2017
Earlier work this paper cites.
Song, S., Yu, F., Zeng, A., Chang, A.X., Savva, M., Funkhouser, T.: Semantic Scene Completion from a Single Depth Image. CVPR (2017)
2017
Earlier work this paper cites.
Tatarchenko, M., Dosovitskiy, A., Brox, T.: Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs. ICCV (2017)
2017
Earlier work this paper cites.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention Is All You Need. NeurIPS (2017)
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
Graham, B., Engelcke, M., Maaten, L.v.d.: 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks. CVPR (2018)
2018
Cited alongside, same era.
Hua, B.S., Tran, M.K., Yeung, S.K.: Pointwise Convolutional Neural Networks. IEEE Conference on Computer Vision and Pattern Recognition (2018)
2018
Cited alongside, same era.
Kato, H., Ushiku, Y., Harada, T.: Neural 3D Mesh Renderer. CVPR (2018)
2018
Cited alongside, same era.
Kendall, A., Gal, Y., Cipolla, R.: Multi-task learning using uncertainty to weigh losses for scene geometry and semantics. CVPR (2018)
2018
Cited alongside, same era.
Li, Y., Bu, R., Sun, M., Wu, W., Di, X., Chen, B.: PointCNN: Convolution On X-Transformed Points. NeurIPS (2018)
2018
Cited alongside, same era.
Chibane, J., Alldieck, T., Pons-Moll, G.: Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion. CVPR (2020)
2020
Later among the works it cites.
Chibane, J., Mir, A., Pons-Moll, G.: Neural Unsigned Distance Fields for Implicit Function Learning. NeurIPS (2020)
2020
Later among the works it cites.
Hu, Q., Yang, B., Xie, L., Rosa, S., Guo, Y., Wang, Z., Trigoni, N., Markham, A.: RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds. CVPR (2020)
2020
Later among the works it cites.
Li, K., Rünz, M., Tang, M., Ma, L., Kong, C., Schmidt, T., Reid, I., Agapito, L., Straub, J., Lovegrove, S., Newcombe, R.: FroDO: From Detections to 3D Objects. CVPR (2020)
2020
Later among the works it cites.
Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. ECCV pp. 405–421 (2020)
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Lin, C.H., Kong, C., Lucey, S.: Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction. AAAI pp. 7114–7121 (2018)
2018
Cited alongside, same era.
Tulsiani, S., Gupta, S., Fouhey, D., Efros, A.A., Malik, J.: Factoring Shape, Pose, and Layout from the 2D Image of a 3D Scene. CVPR (2018)
2018
Cited alongside, same era.
Chen, Z., Zhang, H.: Learning Implicit Fields for Generative Shape Modeling. CVPR (2019)
2019
Cited alongside, same era.
Gkioxari, G., Malik, J., Johnson, J.: Mesh R-CNN. ICCV pp. 9785–9795 (2019)
2019
Cited alongside, same era.
Liu, S., Saito, S., Chen, W., Li, H.: Learning to Infer Implicit Surfaces without 3D Supervision. NeurIPS (2019)
2019
Cited alongside, same era.
Mescheder, L., Oechsle, M., Niemeyer, M., Nowozin, S., Geiger, A.: Occupancy Networks: Learning 3D Reconstruction in Function Space. CVPR pp. 4455–4465 (2019)
2019
Cited alongside, same era.
Park, J.J., Florence, P., Straub, J., Newcombe, R., Lovegrove, S.: DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation. CVPR pp. 165–174 (2019)
2019
Cited alongside, same era.
2020
Later among the works it cites.
Niemeyer, M., Mescheder, L., Oechsle, M., Geiger, A.: Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision. CVPR (2020)
2020
Later among the works it cites.
Peng, S., Niemeyer, M., Mescheder, L., Pollefeys, M., Geiger, A.: Convolutional Occupancy Networks. ECCV pp. 523–540 (2020)
2020
Later among the works it cites.
Yang, B., Wang, S., Markham, A., Trigoni, N.: Robust Attentional Aggregation of Deep Feature Sets for Multi-view 3D Reconstruction. International Journal of Computer Vision 128
2020
Later among the works it cites.
Atzmon, M., Lipman, Y.: SALD: Sign Agnostic Learning with Derivatives. ICLR (2021)
2021
Later among the works it cites.
Luo, A., Li, T., Tai, W.h.Z., Lee, S.: SurfGen : Adversarial 3D Shape Synthesis with Explicit Surface Discriminators. ICCV (2021)
2021
Later among the works it cites.
Ma, B., Han, Z., Liu, Y.s., Zwicker, M.: Neural-Pull : Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces. ICML (2021)
2021
Later among the works it cites.
Niemeyer, M., Geiger, A.: GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields. CVPR pp. 11453–11464 (2021)
2021
Later among the works it cites.
Oechsle, M., Peng, S., Geiger, A.: UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction. ICCV (2021)
2021
Later among the works it cites.
Sucar, E., Liu, S., Ortiz, J., Davison, A.J.: iMAP: Implicit Mapping and Positioning in Real-Time. ICCV (2021)
2021
Later among the works it cites.
Tang, J., Lei, J., Xu, D., Ma, F., Jia, K., Zhang, L.: SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks. ICCV (2021)
2021
Later among the works it cites.
Trevithick, A., Yang, B.: GRF: Learning a General Radiance Field for 3D Representation and Rendering. ICCV (2021)
2021
Later among the works it cites.
Wang, P., Liu, L., Liu, Y., Theobalt, C., Komura, T., Wang, W.: NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction. NeurIPS (2021)
2021
Later among the works it cites.
Zhang, C., Cui, Z., Zhang, Y., Zeng, B., Pollefeys, M., Liu, S.: Holistic 3D Scene Understanding from a Single Image with Implicit Representation. CVPR (2021)
2021
Later among the works it cites.
Zhang, J., Yao, Y., Quan, L.: Learning Signed Distance Field for Multi-view Surface Reconstruction. ICCV (2021)
2021
Later among the works it cites.