PointFlowNet: Learning Representations for Rigid Motion Estimation from Point 
Clouds

Behl, Aseem; Paschalidou, Despoina; Donne, Simon; Geiger, Andreas

doi:10.1109/CVPR.2019.00815

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PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds

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Behl, Aseem
Max Planck Research Group Autonomous Vision, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Paschalidou, Despoina
Max Planck Research Group Autonomous Vision, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Donne, Simon
Max Planck Research Group Autonomous Vision, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Geiger, Andreas
Max Planck Research Group Autonomous Vision, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Behl, A., Paschalidou, D., Donne, S., & Geiger, A. (2019). PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019) (pp. 7954-7963). Piscataway, NJ: IEEE. doi:10.1109/CVPR.2019.00815.

Cite as: https://hdl.handle.net/21.11116/0000-0006-F466-4

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