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On the Continuity of Rotation Representations in Neural Networks

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Ankur Handa: Quaternions and Euler angles are discontinuous and difficult for neural networks to learn. They show 3D rotations have continuous representations in 5D and 6D, which are more suitable for learning. i.e. regress two vectors and apply Graham-Schmidt (GS). https://arxiv.org/abs/1812.07035 https://t.co/fXUF3sgkTT

11 replies, 679 likes


Matt Miesnieks: So this is literally 6D AI ? :) @6d_ai

8 replies, 69 likes


Marc B. Reynolds: This keeps show up in my timeline, so: Quat's are not discontinuous by any normal definition.

4 replies, 14 likes


Chris Choy: I really like this paper from Hao Li's group: On the Continuity of Rotation Representations in Neural Networks, CVPR19 :) https://arxiv.org/pdf/1812.07035.pdf

0 replies, 12 likes


Content

Found on Jan 26 2020 at https://arxiv.org/pdf/1812.07035.pdf

PDF content of a computer science paper: On the Continuity of Rotation Representations in Neural Networks