Gaussian Shell Maps for Efficient 3D Human Generation
Rameen Abdal, Yifan Wang, Zifan Shi, Yinghao Xu, Ryan Po, Zhengfei Kuang, Qifeng Chen, Dit-Yan Yeung, Gordon Wetzstein
2024年份
26顶会引用
摘要
Figure 1 . Gaussian Shell Maps. Gaussian Shell Maps is an efficient framework for 3D human generation connecting 3D Gaussians with CNN-based generators. 3D Gaussians are anchored to "shells" derived from the SMPL template [36] (only two shells are visualized for clarity), and the appearance is modeled in texture space. Trained only on 2D images, we show that our method can generate diverse articulable humans in real-time with state-of-the-art quality directly in high resolution without the need for upsampling and hence avoiding aliasing artifacts.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper26
- GSGAN: Adversarial Learning for Hierarchical Generation of 3D Gaussian SplatsSangeek Hyun, Jae-Pil HeoNeurIPS 2024 · 被引用 17 次
- MPMAvatar: Learning 3D Gaussian Avatars with Accurate and Robust Physics-Based DynamicsChangmin Lee, Jihyun Lee, Tae-Kyun KimNeurIPS 2025 · 被引用 9 次
- CGS-GAN: 3D Consistent Gaussian Splatting GANs for High Resolution Human Head SynthesisFlorian Barthel, Wieland Morgenstern, Paul Hinzer, Anna Hilsmann 等NeurIPS 2025 · 被引用 8 次
- Decoupling Appearance Variations with 3D Consistent Features in Gaussian SplattingJiaqi Lin, Zhihao Li, Binxiao Huang, Xiao Tang 等AAAI 2025 · 被引用 6 次
- E3Gen: Efficient, Expressive and Editable Avatars GenerationWeitian Zhang, Yichao Yan, Yunhui Liu, Xingdong Sheng 等ACM MM 2024 · 被引用 4 次
它引用的顶会 Paper36
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser 等CVPR 2022 · 被引用 13,123 次
- Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingChitwan Saharia, William Chan, Saurabh Saxena, Lala Li 等NeurIPS 2022 · 被引用 8,965 次
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 被引用 5,687 次
- Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance FieldsJonathan T. Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman 等ICCV 2021 · 被引用 2,700 次
- Alias-Free Generative Adversarial NetworksTero Karras, Miika Aittala, Samuli Laine, Erik Härkönen 等NeurIPS 2021 · 被引用 2,126 次
相关 Paper
- GART: Gaussian Articulated Template ModelsJiahui Lei, Yufu Wang, Georgios Pavlakos, Lingjie Liu 等CVPR 2024
- GauHuman: Articulated Gaussian Splatting from Monocular Human VideosShoukang Hu, Tao Hu, Ziwei LiuCVPR 2024
- HumanGaussian: Text-Driven 3D Human Generation with Gaussian SplattingXian Liu, Xiaohang Zhan, Jiaxiang Tang, Ying Shan 等CVPR 2024 · 被引用 42 次
- ASH: Animatable Gaussian Splats for Efficient and Photoreal Human RenderingHaokai Pang, Heming Zhu, Adam Kortylewski, Christian Theobalt 等CVPR 2024 · 被引用 56 次
- Human Gaussian Splatting: Real-Time Rendering of Animatable AvatarsArthur Moreau, Jifei Song, Helisa Dhamo, Richard Shaw 等CVPR 2024 · 被引用 55 次
