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We propose pose-guided multiplane image (MPI) synthesis which can render an animatable character in real scenes with photorealistic quality.
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Balakrishnan, G., Zhao, A., Dalca, A.V., Durand, F., Guttag, J.: Synthesizing images of humans in unseen poses. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 8340–8348 (2018)
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Si, C., Wang, W., Wang, L., Tan, T.: Multistage adversarial losses for pose-based human image synthesis. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 118–126 (2018)
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Wang, T.C., Liu, M.Y., Zhu, J.Y., Tao, A., Kautz, J., Catanzaro, B.: High-resolution image synthesis and semantic manipulation with conditional gans. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 8798–8807 (2018)
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Gao, C., Saraf, A., Kopf, J., Huang, J.B.: Dynamic view synthesis from dynamic monocular video. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 5712–5721 (2021)
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Habermann, M., Liu, L., Xu, W., Zollhoefer, M., Pons-Moll, G., Theobalt, C.: Real-time deep dynamic characters. ACM Transactions on Graphics (TOG) 40
2021
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Li, J., Feng, Z., She, Q., Ding, H., Wang, C., Lee, G.H.: Mine: Towards continuous depth mpi with nerf for novel view synthesis. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 12578–12588 (2021)
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Flynn, J., Broxton, M., Debevec, P., DuVall, M., Fyffe, G., Overbeck, R., Snavely, N., Tucker, R.: Deepview: View synthesis with learned gradient descent. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2367–2376 (2019)
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Guo, K., Lincoln, P., Davidson, P., Busch, J., Yu, X., Whalen, M., Harvey, G., Orts-Escolano, S., Pandey, R., Dourgarian, J., et al.: The relightables: Volumetric performance capture of humans with realistic relighting. ACM Transactions on Graphics (ToG) 38
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Mildenhall, B., Srinivasan, P.P., Ortiz-Cayon, R., Kalantari, N.K., Ramamoorthi, R., Ng, R., Kar, A.: Local light field fusion: Practical view synthesis with prescriptive sampling guidelines. ACM Transactions on Graphics (TOG) 38
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Shysheya, A., Zakharov, E., Aliev, K.A., Bashirov, R., Burkov, E., Iskakov, K., Ivakhnenko, A., Malkov, Y., Pasechnik, I., Ulyanov, D., et al.: Textured neural avatars. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2387–2397 (2019)
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Srinivasan, P.P., Tucker, R., Barron, J.T., Ramamoorthi, R., Ng, R., Snavely, N.: Pushing the boundaries of view extrapolation with multiplane images. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 175–184 (2019)
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Peng, S., Dong, J., Wang, Q., Zhang, S., Shuai, Q., Bao, H., Zhou, X.: Animatable neural radiance fields for human body modeling. arXiv e-prints pp. arXiv–2105 (2021)
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Xu, H., Alldieck, T., Sminchisescu, C.: H-nerf: Neural radiance fields for rendering and temporal reconstruction of humans in motion. Advances in Neural Information Processing Systems 34
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Zhang, J., Liu, X., Ye, X., Zhao, F., Zhang, Y., Wu, M., Zhang, Y., Xu, L., Yu, J.: Editable free-viewpoint video using a layered neural representation. ACM Transactions on Graphics (TOG) 40
2021
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Zhou, X., Zhang, B., Zhang, T., Zhang, P., Bao, J., Chen, D., Zhang, Z., Wen, F.: Cocosnet v2: Full-resolution correspondence learning for image translation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 11465–11475 (2021)
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