LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals
- DOI
- 10.1038/s41592-021-01226-z
- Published
- 2021-08
- Container
- Nature Methods
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41592-021-01226-z,
title = {LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals},
author = {Adam Gosztolai and Semih Günel and Victor Lobato-Ríos and Marco Pietro Abrate and Daniel Morales and Helge Rhodin and Pascal Fua and Pavan Ramdya},
year = {2021},
journal = {Nature Methods},
doi = {10.1038/s41592-021-01226-z},
url = {https://doi.org/10.1038/s41592-021-01226-z}
}RIS
TY - JOUR TI - LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals AU - Adam Gosztolai AU - Semih Günel AU - Victor Lobato-Ríos AU - Marco Pietro Abrate AU - Daniel Morales AU - Helge Rhodin AU - Pascal Fua AU - Pavan Ramdya PY - 2021 JO - Nature Methods DO - 10.1038/s41592-021-01226-z UR - https://doi.org/10.1038/s41592-021-01226-z ER -
APA
Gosztolai, A., Günel, S., Lobato-Ríos, V., Abrate, M. P., Morales, D., Rhodin, H., Fua, P., & Ramdya, P. (2021). LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals. Nature Methods. https://doi.org/10.1038/s41592-021-01226-z
Source records
- crossref · retrieved 2026-09-27T02:08:02.157Z