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DeepLabCut (www.deeplabcut.org) was initially developed by
Alexander & Mackenzie Mathis in collaboration with Matthias Bethge.
DeepLabCut is an open-source tool and has benefited from suggestions and edits by many
individuals including Tanmay Nath, Richard Warren, Ronny Eichler, Jonas Rauber, Hao Wu,
Federico Claudi, Gary Kane, Taiga Abe, and Jonny Saunders as well as the latest author
contributors page for the many additions to this open source project:
https://github.com/AlexEMG/DeepLabCut/graphs/contributors
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DeepLabCut 1.0 Toolbox
A Mathis, [email protected] | https://github.com/AlexEMG/DeepLabCut
M Mathis, [email protected] | https://github.com/MMathisLab
Specific external contributors:
E Insafutdinov and co-authors of DeeperCut (see README) for feature detectors: https://github.com/eldar
- Thus, code in this subdirectory https://github.com/AlexEMG/DeepLabCut/tree/master/deeplabcut/pose_estimation_tensorflow
was adapted from: https://github.com/eldar/pose-tensorflow
Products:
DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nature Neuroscience 2018. DOI
https://doi.org/10.1038/s41593-018-0209-y
A. Mathis, P. Mamidanna, K.M. Cury, T. Abe, V.N. Murthy, M.W. Mathis* & M. Bethge*
Contributions:
Conceptualization: A.M., M.W.M. and M.B.
Software: A.M. and M.W.M.
Formal analysis: A.M.
Experiments: A.M. and V.N.M. (trail-tracking), M.W.M. (mouse reaching), K.M.C. (Drosophila).
Image Labeling: P.M., K.M.C., T.A., M.W.M., A.M.
Writing: A.M. and M.W.M. with input from all authors.
These authors jointly directed this work: M. Mathis, M. Bethge
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DeepLabCut 2.0 Toolbox
A Mathis, [email protected] | https://github.com/AlexEMG/DeepLabCut
T Nath, [email protected] | https://github.com/meet10may
M Mathis, [email protected] | https://github.com/MMathisLab
Products:
Using DeepLabCut for 3D markerless pose estimation across species and behaviors. Nature Protocols, 2019 (in press)
T. Nath*, A. Mathis*, AC. Chen, A. Patel, M. Bethge, M. Mathis
Contributions:
Conceptualization: AM, TN, MWM.
Software: AM, TN and MWM.
Dataset (cheetah): AP.
Image Labeling: ACC.
Formal analysis: ACC, AM and AP analyzed the cheetah data.
Writing: MWM, AM and TN with inputs from all authors.
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