3D-POP - An automated annotation approach to facilitate markerless 2D-3D 
tracking of freely moving birds with marker-based motion capture

Naik, Hemal; Chan, Alex Hoi Hang; Yang, Junran; Delacoux, Mathilde; Couzin, Iain D.; Kano, Fumihiro; Nagy, Mate

doi:10.1109/cvpr52729.2023.02038

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3D-POP - An automated annotation approach to facilitate markerless 2D-3D tracking of freely moving birds with marker-based motion capture

Naik, H., Chan, A. H. H., Yang, J., Delacoux, M., Couzin, I. D., Kano, F., et al. (2023). 3D-POP - An automated annotation approach to facilitate markerless 2D-3D tracking of freely moving birds with marker-based motion capture. 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 21274-21284. doi:10.1109/cvpr52729.2023.02038.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-C37D-B Version Permalink: https://hdl.handle.net/21.11116/0000-000D-C37E-A

Genre: Journal Article

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Creators:
Naik, Hemal¹, Author
Chan, Alex Hoi Hang, Author
Yang, Junran, Author
Delacoux, Mathilde, Author
Couzin, Iain D.¹, Author
Kano, Fumihiro¹, Author
Nagy, Mate¹, Author

Affiliations:
1Department of Collective Behavior, Max Planck Institute of Animal Behavior, Max Planck Society, ou_3054976

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Dates: Date issued: 2023

Publication Status: Issued

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Identifiers: DOI: 10.1109/cvpr52729.2023.02038

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Title: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Source Genre: Journal

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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 21274 - 21284 Identifier: -