DeepLabCut: markerless pose estimation of user-defined body parts with deep learning.

Alexander Mathis, Pranav Mamidanna, Kevin M Cury, Taiga Abe, Venkatesh N Murthy, Mackenzie Weygandt Mathis, Matthias Bethge

September 2018 Nat Neurosci

Synopsis of Social media discussions

The collection highlights widespread support and enthusiasm, exemplified by comments praising user guides, tutorials, and the active user community, with words like 'great', 'active', and 'possible' emphasizing both interest and perceived impact. The tone suggests that the publication is seen as a valuable tool advancing behavioral analysis and digital tracking technologies.

A
Agreement
 Moderate agreement

Most discussions express positive approval and support for the publication, with notes on its usefulness and community engagement.

I
Interest
 High level of interest

The topic garners high interest among users, with mentions of new features, community guides, and technological applications.

E
Engagement
 Moderate level of engagement

Discussions show active participation, sharing resources like tutorials, packages, and questions about implementation.

I
Impact
 Moderate level of impact

The posts suggest that the publication is viewed as influential in the research community, promoting the adoption of markerless pose estimation methods.

Social Mentions

YouTube

6 Videos

Facebook

4 Posts

Twitter

13 Posts

Blogs

9 Articles

News

21 Articles

Metrics

Video Views

150,908

Total Likes

326

Extended Reach

223,299

Social Features

53

Timeline: Posts about article

Top Social Media Posts

Posts referencing the article

DeepLabCut Markerless Pose Estimation with Deep Learning Techniques

DeepLabCut Markerless Pose Estimation with Deep Learning Techniques

This demo shows how to use DeepLabCut in ipython within an Anaconda environment and train the network in Docker, enabling markerless tracking of animal and human body parts with minimal training data.

DeepLabCut

November 11, 2018

54,539 views

Markerless Body Part Tracking Using Deep Learning Techniques

Markerless Body Part Tracking Using Deep Learning Techniques

This video presents a new method for tracking animal and human body parts without physical markers, utilizing deep learning and transfer learning for high accuracy with minimal training data. It offers faster, less invasive behavior analysis.

DeepLabCut

April 11, 2018

39,098 views

DeepLabCut for Markerless Pose Estimation and Behavioral Analysis

DeepLabCut for Markerless Pose Estimation and Behavioral Analysis

DeepLabCut enables tracking of animal and human body parts without physical markers, utilizing deep learning and transfer learning for high accuracy with minimal data. This method facilitates faster, less invasive behavior analysis across species.

DeepLabCut

November 15, 2018

35,351 views

DeepLabCut for Markerless Animal and Human Pose Estimation

DeepLabCut for Markerless Animal and Human Pose Estimation

DeepLabCut utilizes deep learning for markerless tracking of animal and human body parts, reducing the need for physical markers, enabling fast and accurate behavior analysis across species with minimal training data.

DeepLabCut

April 11, 2018

11,852 views

DeepLabCut for Drosophila Egg-Laying Behavior Analysis

DeepLabCut for Drosophila Egg-Laying Behavior Analysis

This video demonstrates DeepLabCut, a markerless pose estimation method that tracks Drosophila egg-laying behavior with minimal training data, across cluttered backgrounds, enabling fast, accurate, and non-invasive behavioral analysis.

DeepLabCut

April 11, 2018

9,774 views

Advances in Animal Pose Estimation with Deep Learning Tools

Advances in Animal Pose Estimation with Deep Learning Tools

This video compares DeepLabCut and SLEAP, exploring their evolution and integration for behavior identification. It highlights how deep learning improves animal pose estimation, enabling quick, accurate tracking across species and behaviors.

NeuroTech

April 8, 2025

296 views

  • ENcenatur
    @encenatur (Twitter)

    DeepLabCut: markerless pose estimation of user-defined body parts with deep learning https://t.co/ABPdLoSqlv
    view full post

    June 6, 2023

  • bbscience
    @bbsience1 (Twitter)

    RT @DeepLabCut: Always great to see nice user-based guides! A great complementary guide to our growing docs and YouTube videos ( https://t.…
    view full post

    March 15, 2021

    1

  • DeepLabCut
    @DeepLabCut (Twitter)

    Always great to see nice user-based guides! A great complementary guide to our growing docs and YouTube videos ( https://t.co/Ys9BaRtopK) thanks @G_HidalgoGadea
    view full post

    March 15, 2021

    13

    1

  • Jana, the Outlier
    @Jana_Ruzickova2 (Twitter)

    @tibor_magura It's great to see that it's possible to do video tracking in R! A couple of years ago one of the students I co-supervised used DeepLabCut (https://t.co/2lodMJhyue) for something similar but R is simply R :) May I know which package you use?
    view full post

    February 22, 2021

    1

  • Alejandra Manjarrez
    @lecteroide (Twitter)

    Aquí un video de cómo una mosquita de la fruta pone un huevo… huevo ingrato que eventualmente se deshará de la herencia materna que ya no necesite. Video de Mackenzie Mathis et al. (no relacionado con la investigación reciente de la enzima Kdo). 4/4 https://t.co/BhUkvpnDRD
    view full post

    July 29, 2020

  • Mackenzie Weygandt Mathis, PhD
    @TrackingActions (Twitter)

    @BohacekLab suppl. here: https://t.co/fIaCeZIDlB
    view full post

    April 18, 2020

    1

  • DeepLabCut
    @DeepLabCut (Twitter)

    @dineshraov No, the Docker is just for training and inference, so I install the simple cpu only version of dlc with conda, see how I use both here: https://t.co/IvFwE91LEA
    view full post

    March 22, 2020

    1

  • Lobsters
    @lobsters (Twitter)

    DeepLabCut: markerless pose estimation of user-defined body parts with deep learning via @sanxiyn https://t.co/DemIBhZkpu #ai #science https://t.co/c9xiw7X4Yw
    view full post

    June 19, 2019

    1

  • Rosaura Brisuela @roswitta.bsky.social
    @Roswitamind (Twitter)

    DeepLabCut: markerless pose estimation of user-defined body parts with deep learning:https://t.co/Sb1jwP5LG3
    view full post

    June 16, 2019

  • Mackenzie Weygandt Mathis, PhD
    @TrackingActions (Twitter)

    @MorphoFun @mechsNmorph @mrmilesvalencia @GlennaClifton There is a very active user community: https://t.co/e2Il9Qeodr and detailed full use-guide: https://t.co/HdC8AfVtDZ plus YouTube Tutorials: https://t.co/0Zgt4sfaBC
    view full post

    March 17, 2019

    2

  • eqs
    @eqseqseqs (Twitter)

    RT @eqseqseqs: #DeepLabCut はてなブログに投稿しました 【論文読み】DeepLabCut: markerless pose estimation of user-defined body parts with deep learning - 反面教師あ…
    view full post

    January 31, 2019

    2

  • Hiroshi Matsui
    @HeathRossie (Twitter)

    RT @eqseqseqs: #DeepLabCut はてなブログに投稿しました 【論文読み】DeepLabCut: markerless pose estimation of user-defined body parts with deep learning - 反面教師あ…
    view full post

    January 31, 2019

    2

  • eqs
    @eqseqseqs (Twitter)

    #DeepLabCut はてなブログに投稿しました 【論文読み】DeepLabCut: markerless pose estimation of user-defined body parts with deep learning - 反面教師あり学習 https://t.co/WyRxJbRQcB #はてなブログ
    view full post

    January 31, 2019

    4

    2

Abstract Synopsis

  • This text explains a new method for tracking animal and human body parts without using physical markers, which can be intrusive and require prior setup.
  • The method uses deep learning, specifically transfer learning, allowing accurate tracking with very little training data, sometimes just 200 labeled frames.
  • It works across different species and behaviors, providing results that are nearly as precise as human observers, making behavior analysis faster and less invasive.]