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In this paper, we introduce the Volumetric Relightable Morphable Model (VRMM), a novel volumetric and parametric facial prior for 3D face modeling.
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The relightables: Volumetric performance capture of humans with realistic relighting
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Disentangled representation learning for 3D face shape. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 11957–11966
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Authentic volumetric avatars from a phone scan
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Relighting4d: Neural relightable human from videos. In European Conference on Computer Vision . Springer, 606–623
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Reconstructing personalized semantic facial nerf models from monocular video
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Headnerf: A real-time nerf-based parametric head model. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 20374–20384
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Zi-Hang Jiang, Qianyi Wu, Keyu Chen, and Juyong Zhang. 2019 · 2019
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A style-based generator architecture for generative adversarial networks. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 4401–4410
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Neural volumes: learning dynamic renderable volumes from images
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Deepsdf: Learning continuous signed distance functions for shape representation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 165–174
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On learning 3D face morphable model from in-the-wild images
Luan Tran and Xiaoming Liu. 2019 · 2019
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AvatarMe: Realistically Renderable 3D Facial Reconstruction" in-the-wild". In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 760–769
Alexandros Lattas, Stylianos Moschoglou, Baris Gecer, Stylianos Ploumpis, Vasileios Triantafyllou, Abhijeet Ghosh, and Stefanos Zafeiriou. 2020 · 2020
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Dynamic facial asset and rig generation from a single scan
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NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. In European Conference on Computer Vision . 405–421
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EyeNeRF: a hybrid representation for photorealistic synthesis, animation and relighting of human eyes
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Instant neural graphics primitives with a multiresolution hash encoding
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Pivotal tuning for latent-based editing of real images
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Morf: Morphable radiance fields for multiview neural head modeling. In ACM SIGGRAPH 2022 Conference Proceedings . 1–9
Daoye Wang, Prashanth Chandran, Gaspard Zoss, Derek Bradley, and Paulo Gotardo. 2022 · 2022
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Multiface: A Dataset for Neural Face Rendering
Cheng-hsin Wuu, Ningyuan Zheng, Scott Ardisson, Rohan Bali, Danielle Belko, Eric Brockmeyer, Lucas Evans, Timothy Godisart, Hyowon Ha, Alexander Hypes, Taylor Koska, Steven Krenn, Stephen Lombardi, Xiaomin Luo, Kevyn McPhail, Laura Millerschoen, Michal Perdoch, Mark Pitts, Alexander Richard, Jason Saragih, Junko Saragih, Takaaki Shiratori, Tomas Simon, Matt Stewart, Autumn Trimble, Xinshuo Weng, David Whitewolf, Chenglei Wu, Shoou-I Yu, and Yaser Sheikh. 2022 · 2022
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Video-driven neural physically-based facial asset for production
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ImFace: A Nonlinear 3D Morphable Face Model with Implicit Neural Representations. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 20343–20352
Mingwu Zheng, Hongyu Yang, Di Huang, and Liming Chen. 2022 · 2022
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Mofanerf: Morphable facial neural radiance field. In European Conference on Computer Vision . Springer, 268–285
Yiyu Zhuang, Hao Zhu, Xusen Sun, and Xun Cao. 2022 · 2022
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Preface: A data-driven volumetric prior for few-shot ultra high-resolution face synthesis. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 3402–3413
Marcel C Bühler, Kripasindhu Sarkar, Tanmay Shah, Gengyan Li, Daoye Wang, Leonhard Helminger, Sergio Orts-Escolano, Dmitry Lagun, Otmar Hilliges, Thabo Beeler, et al · 2023
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Sira: Relightable avatars from a single image. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision . 775–784
Pol Caselles, Eduard Ramon, Jaime Garcia, Xavier Giro-i Nieto, Francesc Moreno-Noguer, and Gil Triginer. 2023 · 2023
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3D Gaussian Splatting for Real-Time Radiance Field Rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis. 2023 · 2023
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Relightify: Relightable 3D Faces from a Single Image via Diffusion Models
Foivos Paraperas Papantoniou, Alexandros Lattas, Stylianos Moschoglou, and Stefanos Zafeiriou. 2023 · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 22500–22510
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman. 2023 · 2023
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Latentavatar: Learning latent expression code for expressive neural head avatar. In ACM SIGGRAPH 2023 Conference Proceedings . 1–10
Yuelang Xu, Hongwen Zhang, Lizhen Wang, Xiaochen Zhao, Han Huang, Guojun Qi, and Yebin Liu. 2023 · 2023
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Towards Practical Capture of High-Fidelity Relightable Avatars. In SIGGRAPH Asia 2023 Conference Proceedings
Haotian Yang, Mingwu Zheng, Wanquan Feng, Haibin Huang, Yu-Kun Lai, Pengfei Wan, Zhongyuan Wang, and Chongyang Ma. 2023 · 2023
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Instant volumetric head avatars. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 4574–4584
Wojciech Zielonka, Timo Bolkart, and Justus Thies. 2023 · 2023
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