We introduce the novel problem of point-level 3D scene interpolation. Given observations of a scene at two distinct states from multiple views, the goal is to synthesize a smooth point-level interpolation between them, without any intermediate supervision. Our method, PAPR in Motion, builds upon the recent Proximity Attention Point Rendering (PAPR) technique, and generates seamless interpolations of both the scene geometry and appearance.
We compare our method to the latest dynamic scene reconstruction method, Dynamic Gaussian, on this task. The results show the point cloud representation of the scene geometry in the first row and the corresponding RGB rendering in the second row.
@inproceedings{peng2024papr,
title={PAPR in Motion: Seamless Point-level 3D Scene Interpolation},
author={Shichong Peng and Yanshu Zhang and Ke Li},
booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2024}
}