A Probabilistic Rotation Representation for Symmetric Shapes With an Efficiently Computable Bingham Loss Function

Author:

Sato Hiroya1,Ikeda Takuya2,Nishiwaki Koichi2

Affiliation:

1. Graduate School of Information Science and Technology, The University of Tokyo,Department of Mechano-Informatics,Bunkyo-ku, Tokyo,Japan,113–8656

2. Woven Planet Holdings, Inc.,Chuo City, Tokyo,Japan,103–0022

Publisher

IEEE

Reference25 articles.

1. Embeddings of real projective spaces;davis;Boletin de la Sociedad Matematica Mexicana,1998

2. On the Continuity of Rotation Representations in Neural Networks

3. 6D Camera Relocalization in Ambiguous Scenes via Continuous Multimodal Inference

4. An analysis of SVD for deep rotation estimation;jake;Advances in neural information processing systems,2020

5. Geometry-aware learning of maps for camera localization;samarth;IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2018

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