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Creating relightable and animatable avatars from multi-view or monocular videos is a challenging task for digital human creation and virtual reality applications.
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2022
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T. Jiang, X. Chen, J. Song, and O. Hilliges, “Instantavatar: Learning avatars from monocular video in 60 seconds,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 16 922–16 932
2023
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D. Xiang, T. Bagautdinov, T. Stuyck, F. Prada, J. Romero, W. Xu, S. Saito, J. Guo, B. Smith, T. Shiratori et al. , “Dressing avatars: Deep photorealistic appearance for physically simulated clothing,” ACM Transactions on Graphics (TOG) , vol. 41, no. 6, pp. 1–15, 2022
2022
Cited alongside, same era.
C.-Y. Weng, B. Curless, P. P. Srinivasan, J. T. Barron, and I. Kemelmacher-Shlizerman, “Humannerf: Free-viewpoint rendering of moving people from monocular video,” in Proceedings of the IEEE/CVF conference on computer vision and pattern Recognition , 2022, pp. 16 210–16 220
2022
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S. Wang, K. Schwarz, A. Geiger, and S. Tang, “Arah: Animatable volume rendering of articulated human sdfs,” in European conference on computer vision . Springer, 2022, pp. 1–19
2022
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W. Jiang, K. M. Yi, G. Samei, O. Tuzel, and A. Ranjan, “Neuman: Neural human radiance field from a single video,” in European Conference on Computer Vision . Springer, 2022, pp. 402–418
2022
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Z. Zheng, H. Huang, T. Yu, H. Zhang, Y. Guo, and Y. Liu, “Structured local radiance fields for human avatar modeling,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 15 893–15 903
2022
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G. Yang, M. Vo, N. Neverova, D. Ramanan, A. Vedaldi, and H. Joo, “Banmo: Building animatable 3d neural models from many casual videos,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 2863–2873
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2023
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Y. Liu, P. Wang, C. Lin, X. Long, J. Wang, L. Liu, T. Komura, and W. Wang, “Nero: Neural geometry and brdf reconstruction of reflective objects from multiview images,” ACM Transactions on Graphics (ToG) , vol. 42, no. 4, pp. 1–22, 2023
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W. Sun, Y. Che, H. Huang, and Y. Guo, “Neural reconstruction of relightable human model from monocular video,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 397–407
2023
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U. Iqbal, A. Caliskan, K. Nagano, S. Khamis, P. Molchanov, and J. Kautz, “Rana: Relightable articulated neural avatars,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 23 142–23 153
2023
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M. Işık, M. Rünz, M. Georgopoulos, T. Khakhulin, J. Starck, L. Agapito, and M. Nießner, “Humanrf: High-fidelity neural radiance fields for humans in motion,” ACM Transactions on Graphics (TOG) , vol. 42, no. 4, pp. 1–12, 2023
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Z. Zheng, X. Zhao, H. Zhang, B. Liu, and Y. Liu, “Avatarrex: Real-time expressive full-body avatars,” ACM Transactions on Graphics (TOG) , vol. 42, no. 4, pp. 1–19, 2023
2023
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S. Saito, G. Schwartz, T. Simon, J. Li, and G. Nam, “Relightable gaussian codec avatars,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2024, pp. 130–141
2024
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S. Wang, B. Antic, A. Geiger, and S. Tang, “Intrinsicavatar: Physically based inverse rendering of dynamic humans from monocular videos via explicit ray tracing,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2024, pp. 1877–1888
2024
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W. Lin, C. Zheng, J.-H. Yong, and F. Xu, “Relightable and animatable neural avatars from videos,” in Proceedings of the AAAI Conference on Artificial Intelligence , vol. 38, no. 4, 2024, pp. 3486–3494
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Y. Chen, Z. Zheng, Z. Li, C. Xu, and Y. Liu, “Meshavatar: Learning high-quality triangular human avatars from multi-view videos,” in European Conference on Computer Vision . Springer, 2024, pp. 250–269
2024
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