NeurMiPs: Neural Mixture of Planar Experts for View Synthesis
Zhi-Hao Lin, Wei-Chiu Ma, Hao-Yu Hsu, Yu-Chiang Frank Wang, Shenlong Wang
摘要
We present Neural Mixtures of Planar Experts (Neur-MiPs), a novel planar-based scene representation for modeling geometry and appearance. NeurMiPs leverages a collection of local planar experts in 3D space as the scene representation. Each planar expert consists of the parameters of the local rectangular shape representing geometry and a neural radiance field modeling the color and opacity. We render novel views by calculating ray-plane intersections and composite output colors and densities at intersected points to the image. NeurMiPs blends the efficiency of explicit mesh rendering and flexibility of the neural radiance field. Experiments demonstrate superior performance and speed of our proposed method, compared to other 3D representations in novel view synthesis.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,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 Paper18
- MERF: Memory-Efficient Radiance Fields for Real-time View Synthesis in Unbounded ScenesChristian Reiser, Richard Szeliski, Dor Verbin, Pratul P. Srinivasan 等SIGGRAPH 2023 · 被引用 194 次
- PhysGaussian: Physics-Integrated 3D Gaussians for Generative DynamicsTianyi Xie, Zeshun Zong, Yuxing Qiu, Xuan Li 等CVPR 2024 · 被引用 118 次
- StegaNeRF: Embedding Invisible Information within Neural Radiance FieldsChenxin Li, Brandon Y. Feng, Zhiwen Fan, Panwang Pan 等ICCV 2023 · 被引用 57 次
- ClimateNeRF: Extreme Weather Synthesis in Neural Radiance FieldYuan Li, Zhi-Hao Lin, David A. Forsyth, Jia-Bin Huang 等ICCV 2023 · 被引用 44 次
- GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-MeshJing Wen, Xiaoming Zhao, Zhongzheng Ren, Alexander G. Schwing 等CVPR 2024 · 被引用 33 次
它引用的顶会 Paper25
- Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional DomainsMatthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil 等NeurIPS 2020 · 被引用 4,036 次
- Neural Sparse Voxel FieldsLingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua 等NeurIPS 2020 · 被引用 1,535 次
- Volume Rendering of Neural Implicit SurfacesLior Yariv, Jiatao Gu, Yoni Kasten, Yaron LipmanNeurIPS 2021 · 被引用 1,421 次
- PlenOctrees for Real-time Rendering of Neural Radiance FieldsAlex Yu, Ruilong Li, Matthew Tancik, Hao Li 等ICCV 2021 · 被引用 1,284 次
- Multiview Neural Surface Reconstruction by Disentangling Geometry and AppearanceLior Yariv, Yoni Kasten, Dror Moran, Meirav Galun 等NeurIPS 2020 · 被引用 1,010 次
相关 Paper
- GRF: Learning a General Radiance Field for 3D Representation and RenderingAlex Trevithick, Bo YangICCV 2021 · 被引用 258 次
- MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile ArchitecturesZhiqin Chen, Thomas A. Funkhouser, Peter Hedman, Andrea TagliasacchiCVPR 2023
- Urban Radiance Field Representation with Deformable Neural Mesh PrimitivesFan Lu, Yan Xu, Guang Chen, Hongsheng Li 等ICCV 2023 · 被引用 64 次
- Tetra-NeRF: Representing Neural Radiance Fields Using TetrahedraJonas Kulhanek, Torsten SattlerICCV 2023 · 被引用 73 次
- HyRF: Hybrid Radiance Fields for Memory-efficient and High-quality Novel View SynthesisZipeng Wang, Dan XuNeurIPS 2025 · 被引用 5 次
