2020
Probabilistic Orientation Estimation with Matrix Fisher Distributions
NeurIPS 2020poster
This paper focuses on estimating probability distributions over the set of 3D ro- tations (SO(3)) using deep neural networks. Learning to regress models to the set of rotations is inherently difficult due to differences in topology between R^N and SO(3). We overcome this issue by using a neural netw…