@inproceedings{6b5f606411ab4653807ddca00b3c7477,
title = "NeurMiPs: Neural Mixture of Planar Experts for View Synthesis",
abstract = "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.",
keywords = "3D from multi-view and sensors, Vision + graphics",
author = "Lin, {Zhi Hao} and Ma, {Wei Chiu} and Hsu, {Hao Yu} and Wang, {Yu Chiang Frank} and Shenlong Wang",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022 ; Conference date: 19-06-2022 Through 24-06-2022",
year = "2022",
doi = "10.1109/CVPR52688.2022.01525",
language = "English (US)",
series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
publisher = "IEEE Computer Society",
pages = "15681--15691",
booktitle = "Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022",
}