CVPR2021
Online Learning of a Probabilistic and Adaptive Scene Representation
Zike Yan, Xin Wang, Hongbin Zha
Abstract
Figure 1: We propose a continuous probability field that can be learned incrementally from streaming data. The probabilistic formulation naturally incorporates both geometry and uncertainty information into a compact parameter space. The generative characteristic allows convenient conversion to different kinds of scene representations.