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We learn a self-supervised, single-view 3D reconstruction model that predicts the 3D mesh shape, texture and camera pose of a target object with a collection of 2D images and silhouettes.
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Pepik, B., Gehler, P., Stark, M., Schiele, B.: 3d 2 pm–3d deformable part models. In: ECCV (2012)
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Xiang, Y., Mottaghi, R., Savarese, S.: Beyond pascal: A benchmark for 3d object detection in the wild. In: WACV (2014)
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Choy, C.B., Xu, D., Gwak, J., Chen, K., Savarese, S.: 3d-r2n2: A unified approach for single and multi-view 3d object reconstruction. In: ECCV (2016)
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Girdhar, R., Fouhey, D., Rodriguez, M., Gupta, A.: Learning a predictable and generative vector representation for objects. In: ECCV (2016)
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He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR (2016)
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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: CVPR (2016)
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Rezende, D.J., Eslami, S.A., Mohamed, S., Battaglia, P., Jaderberg, M., Heess, N.: Unsupervised learning of 3d structure from images. In: NeurIPS (2016)
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Wu, J., Zhang, C., Xue, T., Freeman, W.T., Tenenbaum, J.B.: Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling. In: NeurIPS (2016)
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Xiang, Y., Kim, W., Chen, W., Ji, J., Choy, C., Su, H., Mottaghi, R., Guibas, L., Savarese, S.: Objectnet3d: A large scale database for 3d object recognition. In: ECCV (2016)
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Yan, X., Yang, J., Yumer, E., Guo, Y., Lee, H.: Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision. In: NeurIPS (2016)
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Yan, X., Yang, J., Yumer, E., Guo, Y., Lee, H.: Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision. In: NeurIPS (2016)
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Fan, H., Su, H., Guibas, L.J.: A point set generation network for 3d object reconstruction from a single image. In: CVPR (2017)
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Gwak, J., Choy, C.B., Chandraker, M., Garg, A., Savarese, S.: Weakly supervised 3d reconstruction with adversarial constraint. In: 3DV (2017)
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Häne, C., Tulsiani, S., Malik, J.: Hierarchical surface prediction for 3d object reconstruction. In: 3DV (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: NeurIPS (2017)
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Simon, T., Joo, H., Matthews, I., Sheikh, Y.: Hand keypoint detection in single images using multiview bootstrapping. In: CVPR (2017)
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Thewlis, J., Bilen, H., Vedaldi, A.: Unsupervised learning of object landmarks by factorized spatial embeddings. In: ICCV (2017)
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Wang, N., Zhang, Y., Li, Z., Fu, Y., Liu, W., Jiang, Y.G.: Pixel2mesh: Generating 3d mesh models from single rgb images. In: ECCV (2018)
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Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: CVPR (2018)
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Zhang, Y., Guo, Y., Jin, Y., Luo, Y., He, Z., Lee, H.: Unsupervised discovery of object landmarks as structural representations. In: CVPR (2018)
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Zhu, J.Y., Zhang, Z., Zhang, C., Wu, J., Torralba, A., Tenenbaum, J., Freeman, W.: Visual object networks: Image generation with disentangled 3D representations. In: NeurIPS (2018)
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Chen, W., Gao, J., Ling, H., Smith, E., Lehtinen, J., Jacobson, A., Fidler, S.: Learning to predict 3d objects with an interpolation-based differentiable renderer. In: NeurIPS (2019)
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Tulsiani, S., Zhou, T., Efros, A.A., Malik, J.: Multi-view supervision for single-view reconstruction via differentiable ray consistency. In: CVPR (2017)
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2017
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Collins, E., Achanta, R., Susstrunk, S.: Deep feature factorization for concept discovery. In: ECCV (2018)
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Henderson, P., Ferrari, V.: Learning to generate and reconstruct 3d meshes with only 2d supervision. In: BMVC (2018)
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Honari, S., Molchanov, P., Tyree, S., Vincent, P., Pal, C., Kautz, J.: Improving landmark localization with semi-supervised learning. In: CVPR (2018)
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Insafutdinov, E., Dosovitskiy, A.: Unsupervised learning of shape and pose with differentiable point clouds. In: NeurIPS (2018)
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2019
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Gkioxari, G., Malik, J., Johnson, J.: Mesh r-cnn. ICCV (2019)
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Henderson, P., Ferrari, V.: Learning single-image 3d reconstruction by generative modelling of shape, pose and shading. IJCV (2019)
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Hung, W.C., Jampani, V., Liu, S., Molchanov, P., Yang, M.H., Kautz, J.: Scops: Self-supervised co-part segmentation. In: CVPR (2019)
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Kato, H., Harada, T.: Learning view priors for single-view 3d reconstruction. In: CVPR (2019)
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Kulkarni, N., Gupta, A., Tulsiani, S.: Canonical surface mapping via geometric cycle consistency. In: ICCV (2019)
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Liu, S., Li, T., Chen, W., Li, H.: Soft rasterizer: A differentiable renderer for image-based 3d reasoning. In: ICCV (2019)
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Liu, S., Saito, S., Chen, W., Li, H.: Learning to infer implicit surfaces without 3d supervision. In: NeurIPS (2019)
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Mescheder, L., Oechsle, M., Niemeyer, M., Nowozin, S., Geiger, A.: Occupancy networks: Learning 3d reconstruction in function space. In: CVPR (2019)
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Pan, J., Han, X., Chen, W., Tang, J., Jia, K.: Deep mesh reconstruction from single rgb images via topology modification networks. In: ICCV (2019)
2019
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Wen, C., Zhang, Y., Li, Z., Fu, Y.: Pixel2mesh++: Multi-view 3d mesh generation via deformation. In: ICCV (2019)
2019
Later among the works it cites.