Fetching the paper…
Reading the bibliography…
We introduce SparseNeuS, a novel neural rendering based method for the task of surface reconstruction from multi-view images.
Seitz, S.M., Dyer, C.R.: Photorealistic scene reconstruction by voxel coloring. International Journal of Computer Vision 35
1999
Earlier work this paper cites.
Kutulakos, K.N., Seitz, S.M.: A theory of shape by space carving. International journal of computer vision 38
2000
Earlier work this paper cites.
Lhuillier, M., Quan, L.: A quasi-dense approach to surface reconstruction from uncalibrated images. IEEE transactions on pattern analysis and machine intelligence 27
2005
Earlier work this paper cites.
Campbell, N.D., Vogiatzis, G., Hernández, C., Cipolla, R.: Using multiple hypotheses to improve depth-maps for multi-view stereo. In: European Conference on Computer Vision. pp. 766–779. Springer (2008)
2008
Earlier work this paper cites.
Furukawa, Y., Ponce, J.: Accurate, dense, and robust multiview stereopsis. IEEE transactions on pattern analysis and machine intelligence 32
2009
Earlier work this paper cites.
Tola, E., Strecha, C., Fua, P.: Efficient large-scale multi-view stereo for ultra high-resolution image sets. Machine Vision and Applications 23
2012
Earlier work this paper cites.
Kazhdan, M., Hoppe, H.: Screened poisson surface reconstruction. ACM Transactions on Graphics (ToG) 32
2013
Earlier work this paper cites.
Jensen, R., Dahl, A., Vogiatzis, G., Tola, E., Aanæs, H.: Large scale multi-view stereopsis evaluation. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 406–413 (2014)
2014
Earlier work this paper cites.
Galliani, S., Lasinger, K., Schindler, K.: Massively parallel multiview stereopsis by surface normal diffusion. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 873–881 (2015)
2015
Earlier work this paper cites.
Schonberger, J.L., Frahm, J.M.: Structure-from-motion revisited. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 4104–4113 (2016)
2016
Earlier work this paper cites.
Schönberger, J.L., Zheng, E., Frahm, J.M., Pollefeys, M.: Pixelwise view selection for unstructured multi-view stereo. In: European Conference on Computer Vision. pp. 501–518. Springer (2016)
2016
Earlier work this paper cites.
Ji, M., Gall, J., Zheng, H., Liu, Y., Fang, L.: Surfacenet: An end-to-end 3d neural network for multiview stereopsis. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 2307–2315 (2017)
2017
Earlier work this paper cites.
Kar, A., Häne, C., Malik, J.: Learning a multi-view stereo machine. Advances in neural information processing systems 30
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: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 2117–2125 (2017)
2017
Earlier work this paper cites.
Yao, Y., Luo, Z., Li, S., Fang, T., Quan, L.: Mvsnet: Depth inference for unstructured multi-view stereo. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 767–783 (2018)
2018
Earlier work this paper cites.
Chen, Z., Zhang, H.: Learning implicit fields for generative shape modeling. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 5939–5948 (2019)
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
Mescheder, L., Oechsle, M., Niemeyer, M., Nowozin, S., Geiger, A.: Occupancy networks: Learning 3d reconstruction in function space. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 4460–4470 (2019)
2019
Earlier work this paper cites.
Michalkiewicz, M., Pontes, J.K., Jack, D., Baktashmotlagh, M., Eriksson, A.: Implicit surface representations as layers in neural networks. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 4743–4752 (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. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 165–174 (2019)
2019
Cited alongside, same era.
Saito, S., Huang, Z., Natsume, R., Morishima, S., Kanazawa, A., Li, H.: Pifu: Pixel-aligned implicit function for high-resolution clothed human digitization. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2304–2314 (2019)
2019
Cited alongside, same era.
Sitzmann, V., Thies, J., Heide, F., Nießner, M., Wetzstein, G., Zollhofer, M.: Deepvoxels: Learning persistent 3d feature embeddings. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2437–2446 (2019)
Yao, Y., Luo, Z., Li, S., Zhang, J., Ren, Y., Zhou, L., Fang, T., Quan, L.: Blendedmvs: A large-scale dataset for generalized multi-view stereo networks. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 1790–1799 (2020)
2020
Later among the works it cites.
Yariv, L., Kasten, Y., Moran, D., Galun, M., Atzmon, M., Ronen, B., Lipman, Y.: Multiview neural surface reconstruction by disentangling geometry and appearance. Advances in Neural Information Processing Systems 33
2020
Later among the works it cites.
Chen, A., Xu, Z., Zhao, F., Zhang, X., Xiang, F., Yu, J., Su, H.: Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 14124–14133 (2021)
2021
Later among the works it cites.
Chibane, J., Bansal, A., Lazova, V., Pons-Moll, G.: Stereo radiance fields (srf): Learning view synthesis for sparse views of novel scenes. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 7911–7920 (2021)
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2019
Cited alongside, same era.
Sitzmann, V., Zollhöfer, M., Wetzstein, G.: Scene representation networks: Continuous 3d-structure-aware neural scene representations. Advances in Neural Information Processing Systems 32
2019
Cited alongside, same era.
Yao, Y., Luo, Z., Li, S., Shen, T., Fang, T., Quan, L.: Recurrent mvsnet for high-resolution multi-view stereo depth inference. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 5525–5534 (2019)
2019
Cited alongside, same era.
Atzmon, M., Lipman, Y.: Sal: Sign agnostic learning of shapes from raw data. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2565–2574 (2020)
2020
Cited alongside, same era.
2020
Cited alongside, same era.
Gu, X., Fan, Z., Zhu, S., Dai, Z., Tan, F., Tan, P.: Cascade cost volume for high-resolution multi-view stereo and stereo matching. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2495–2504 (2020)
2020
Cited alongside, same era.
Ji, M., Zhang, J., Dai, Q., Fang, L.: Surfacenet+: An end-to-end 3d neural network for very sparse multi-view stereopsis. IEEE Transactions on Pattern Analysis and Machine Intelligence 43
2020
Cited alongside, same era.
Jiang, Y., Ji, D., Han, Z., Zwicker, M.: Sdfdiff: Differentiable rendering of signed distance fields for 3d shape optimization. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 1251–1261 (2020)
2020
Cited alongside, same era.
Liu, L., Gu, J., Zaw Lin, K., Chua, T.S., Theobalt, C.: Neural sparse voxel fields. Advances in Neural Information Processing Systems 33
2020
Cited alongside, same era.
2021
Later among the works it cites.
2021
Later among the works it cites.
Kellnhofer, P., Jebe, L.C., Jones, A., Spicer, R., Pulli, K., Wetzstein, G.: Neural lumigraph rendering. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 4287–4297 (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
Long, X., Lin, C., Liu, L., Li, W., Theobalt, C., Yang, R., Wang, W.: Adaptive surface normal constraint for depth estimation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 12849–12858 (2021)
2021
Later among the works it cites.
Long, X., Liu, L., Li, W., Theobalt, C., Wang, W.: Multi-view depth estimation using epipolar spatio-temporal networks. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 8258–8267 (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. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 5589–5599 (2021)
2021
Later among the works it cites.
Sun, J., Xie, Y., Chen, L., Zhou, X., Bao, H.: Neuralrecon: Real-time coherent 3d reconstruction from monocular video. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 15598–15607 (2021)
2021
Later among the works it cites.
Trevithick, A., Yang, B.: Grf: Learning a general radiance field for 3d representation and rendering. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 15182–15192 (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. Advances in Neural Information Processing Systems 34
2021
Later among the works it cites.
Wang, Q., Wang, Z., Genova, K., Srinivasan, P.P., Zhou, H., Barron, J.T., Martin-Brualla, R., Snavely, N., Funkhouser, T.: Ibrnet: Learning multi-view image-based rendering. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 4690–4699 (2021)
2021
Later among the works it cites.
Yariv, L., Gu, J., Kasten, Y., Lipman, Y.: Volume rendering of neural implicit surfaces. Advances in Neural Information Processing Systems 34
2021
Later among the works it cites.
Yu, A., Ye, V., Tancik, M., Kanazawa, A.: pixelnerf: Neural radiance fields from one or few images. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 4578–4587 (2021)
2021
Later among the works it cites.
Zhang, J., Yao, Y., Quan, L.: Learning signed distance field for multi-view surface reconstruction. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 6525–6534 (2021)
2021
Later among the works it cites.