Fast animal pose estimation using deep neural networks.

Talmo D Pereira, Diego E Aldarondo, Lindsay Willmore, Mikhail Kislin, Samuel S-H Wang, Mala Murthy, Joshua W Shaevitz

January 2019

Synopsis of Social media discussions

The posts clearly convey enthusiasm, using words like 'amazing' and phrases such as 'the future,' which underline high interest and perceived impact; these expressions show strong alignment with the research's implications for advancing animal pose estimation technologies.

A
Agreement
 Strong agreement

The posts express strong support for the publication, highlighting LEAP as an innovative and forward-looking method.

I
Interest
 High level of interest

The discussions demonstrate high interest, emphasizing the novelty and potential of the system.

E
Engagement
 Moderate level of engagement

Posts actively engage with the implications of the research, praising it as 'amazing' and 'the way of the future', indicating meaningful engagement.

I
Impact
 High level of impact

The posts reflect that the publication has significant potential to influence future research and methodologies in animal pose estimation.

Social Mentions

YouTube

2 Videos

Twitter

3 Posts

Blogs

3 Articles

News

6 Articles

Metrics

Video Views

2,810

Total Likes

31

Extended Reach

8,120

Social Features

14

Timeline: Posts about article

Top Social Media Posts

Posts referencing the article

Fast Animal Pose Estimation Using Deep Neural Networks in Mice and Flies

Fast Animal Pose Estimation Using Deep Neural Networks in Mice and Flies

LEAP is a deep learning tool for quick, accurate animal pose estimation, capable of predicting multiple body points with minimal training data, validated on fruit flies and mice.

Francis Villatoro

February 6, 2019

2,514 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)

    Fast animal pose estimation using deep neural networks https://t.co/rwdErUS29s
    view full post

    June 6, 2023

  • sama ahmed
    @ColumboAhmed (Twitter)

    RT @BalintZKacsoh: "Fast animal pose estimation using deep neural networks" from @talmop et al. Amazing paper! LEAP is the way of the futur…
    view full post

    January 8, 2019

    1

  • Balint Z. Kacsoh
    @BalintZKacsoh (Twitter)

    "Fast animal pose estimation using deep neural networks" from @talmop et al. Amazing paper! LEAP is the way of the future! https://t.co/iVMi2UXEwh
    view full post

    January 8, 2019

    3

    1

Abstract Synopsis

  • LEAP is a deep learning-based tool designed for quick and accurate animal pose estimation, capable of predicting positions of various body parts with minimal training data.
  • The system includes a graphical interface for labeling and training, and can deliver fast predictions on new data, achieving high accuracy with as few as 100 frames.
  • LEAP has been validated on videos of fruit flies and mice, successfully tracking multiple body points, reproducing known behaviors, and even working in complex imaging conditions.]