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3D reconstruction is a fundamental problem in computer vision, and the task is especially challenging when the object to reconstruct is partially or fully occluded.
Waltz, D.: Understanding Line Drawings of Scenes with Shadows. In: The Psychology of Computer Vision. p. pages. McGraw-Hill (1975)
1975
Earlier work this paper cites.
Shafer, S.A., Kanade, T.: Using shadows in finding surface orientations. Computer Vision, Graphics, and Image Processing 22
1983
Earlier work this paper cites.
Horry, Y., Anjyo, K.I., Arai, K.: Tour into the picture: using a spidery mesh interface to make animation from a single image. In: Proceedings of the 24th annual conference on Computer graphics and interactive techniques. pp. 225–232 (1997)
1997
Earlier work this paper cites.
Bouguet, J.Y., Perona, P.: 3d photography using shadows in dual-space geometry. International Journal of Computer Vision 35
1999
Earlier work this paper cites.
De Bonet, J.S., Viola, P.: Poxels: Probabilistic voxelized volume reconstruction. In: Proceedings of International Conference on Computer Vision (ICCV). pp. 418–425. Citeseer (1999)
1999
Earlier work this paper cites.
Seitz, S.M., Dyer, C.R.: Photorealistic scene reconstruction by voxel coloring. International Journal of Computer Vision 35
1999
Earlier work this paper cites.
Broadhurst, A., Drummond, T.W., Cipolla, R.: A probabilistic framework for space carving. In: Proceedings eighth IEEE international conference on computer vision. ICCV 2001. vol. 1, pp. 388–393. IEEE (2001)
2001
Earlier work this paper cites.
Hartley, R., Zisserman, A.: Multiple view geometry in computer vision. Cambridge university press (2003)
2003
Earlier work this paper cites.
Troccoli, A., Allen, P.: A Shadow Based Method for Image to Model Registration. In: 2004 Conference on Computer Vision and Pattern Recognition Workshop. pp. 169–169 (Jun 2004). https://doi.org/10.1109/CVPR.2004.289
2004
Earlier work this paper cites.
Hoiem, D., Efros, A.A., Hebert, M.: Automatic photo pop-up. In: ACM SIGGRAPH 2005 Papers, pp. 577–584 (2005)
2005
Earlier work this paper cites.
2005
Earlier work this paper cites.
Seitz, S.M., Curless, B., Diebel, J., Scharstein, D., Szeliski, R.: A comparison and evaluation of multi-view stereo reconstruction algorithms. In: 2006 IEEE computer society conference on computer vision and pattern recognition (CVPR’06). vol. 1, pp. 519–528. IEEE (2006)
2006
Earlier work this paper cites.
Yuille, A., Kersten, D.: Vision as bayesian inference: analysis by synthesis? Trends in cognitive sciences 10
2006
Earlier work this paper cites.
Savarese, S., Andreetto, M., Rushmeier, H., Bernardini, F., Perona, P.: 3D Reconstruction by Shadow Carving: Theory and Practical Evaluation. International Journal of Computer Vision 71
2007
Earlier work this paper cites.
Agarwal, S., Snavely, N., Seitz, S.M., Szeliski, R.: Bundle adjustment in the large. In: European conference on computer vision. pp. 29–42. Springer (2010)
2010
Earlier work this paper cites.
Bleyer, M., Rhemann, C., Rother, C.: Patchmatch stereo-stereo matching with slanted support windows. In: Bmvc. vol. 11, pp. 1–11 (2011)
2011
Cited alongside, same era.
Welling, M., Teh, Y.W.: Bayesian learning via stochastic gradient langevin dynamics. In: Proceedings of the 28th international conference on machine learning (ICML-11). pp. 681–688. Citeseer (2011)
2011
Cited alongside, same era.
Ionescu, C., Papava, D., Olaru, V., Sminchisescu, C.: Human3.6m: Large scale datasets and predictive methods for 3d human sensing in natural environments. IEEE Transactions on Pattern Analysis and Machine Intelligence 36
2014
Cited alongside, same era.
2015
Cited alongside, same era.
Shin, D., Fowlkes, C.C., Hoiem, D.: Pixels, Voxels, and Views: A Study of Shape Representations for Single View 3D Object Shape Prediction. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 3061–3069. IEEE, Salt Lake City, UT (Jun 2018). https://doi.org/10.1109/CVPR.2018.00323, https://ieeexplore.ieee.org/document/8578421/
2018
Later among the works it cites.
Kanazawa, A., Zhang, J.Y., Felsen, P., Malik, J.: Learning 3d human dynamics from video. In: Computer Vision and Pattern Regognition (CVPR) (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. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 7708–7717 (2019)
2019
Later among the works it 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)
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2015
Cited alongside, same era.
Krull, A., Brachmann, E., Michel, F., Yang, M.Y., Gumhold, S., Rother, C.: Learning analysis-by-synthesis for 6d pose estimation in rgb-d images. In: Proceedings of the IEEE international conference on computer vision. pp. 954–962 (2015)
2015
Cited alongside, same era.
2016
Cited alongside, same era.
2016
Cited alongside, same era.
Galliani, S., Lasinger, K., Schindler, K.: Gipuma: Massively parallel multi-view stereo reconstruction. Publikationen der Deutschen Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation e. V 25
2016
Cited alongside, same era.
Kim, J., Lee, J.K., Lee, K.M.: Accurate Image Super-Resolution Using Very Deep Convolutional Networks. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1646–1654. IEEE, Las Vegas, NV, USA (Jun 2016). https://doi.org/10.1109/CVPR.2016.182, http://ieeexplore.ieee.org/document/7780551/
2016
Cited alongside, same era.
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
Cited alongside, same era.
Groueix, T., Fisher, M., Kim, V.G., Russell, B.C., Aubry, M.: A papier-mâché approach to learning 3d surface generation. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 216–224 (2018)
2018
Cited alongside, same era.
2019
Later among the works it cites.
Goel, S., Kanazawa, A., , Malik, J.: Shape and viewpoints without keypoints. In: ECCV (2020)
2020
Later among the works it cites.
Li, X., Liu, S., Kim, K., Mello, S.D., Jampani, V., Yang, M.H., Kautz, J.: Self-supervised single-view 3d reconstruction via semantic consistency. In: European Conference on Computer Vision. pp. 677–693. Springer (2020)
2020
Later among the works it cites.
Menon, S., Damian, A., Hu, S., Ravi, N., Rudin, C.: Pulse: Self-supervised photo upsampling via latent space exploration of generative models. In: Proceedings of the ieee/cvf conference on computer vision and pattern recognition. pp. 2437–2445 (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. In: European conference on computer vision. pp. 405–421. Springer (2020)
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. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 3504–3515 (2020)
2020
Later among the works it cites.
Wang, T., Hu, X., Wang, Q., Heng, P.A., Fu, C.W.: Instance Shadow Detection. In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1877–1886. IEEE, Seattle, WA, USA (Jun 2020). https://doi.org/10.1109/CVPR42600.2020.00195, https://ieeexplore.ieee.org/document/9157490/
2020
Later among the works it cites.
Wu, S., Rupprecht, C., Vedaldi, A.: Unsupervised learning of probably symmetric deformable 3d objects from images in the wild. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 1–10 (2020)
2020
Later among the works it cites.
Ye, Y., Tulsiani, S., Gupta, A.: Shelf-supervised mesh prediction in the wild. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 8843–8852 (2021)
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: CVPR (2021)
2021
Later among the works it cites.
Sadekar, K., Tiwari, A., Raman, S.: Shadow art revisited: a differentiable rendering based approach. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 29–37 (2022)
2022
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