---
license: apache-2.0
tags:
- computer_vision
- pose_estimation
- animal_pose_estimation
- deeplabcut
---

# DeepLabCut - Model Backbones

This repository contains backbone weights for [DeepLabCut](
https://github.com/DeepLabCut/DeepLabCut) models [1]. These weights are downloaded
automatically in DeepLabCut when a model architecture requiring them is used.

## Backbone Architectures

### CSPNeXt

The CSPNeXt backbone was first introduced in _RTMDet: An Empirical Study of Designing 
Real-Time Object Detectors_ [2], and then used in _RTMPose: Real-Time Multi-Person Pose
Estimation based on MMPose_ [3]. These model weights are adapted from the [CSPNeXt 
weights pre-trained on 7 public human pose estimation benchmarks](
https://github.com/open-mmlab/mmpose/tree/main/projects/rtmpose#pretrained-models) 
released with the RTMPose models. Available variants are `CSPNeXT-s`, `CSPNeXT-m`, and 
`CSPNeXT-x`.

## References

1. Alexander Mathis, Pranav Mamidanna, Kevin M. Cury, Taiga Abe, Venkatesh N. Murthy, 
Mackenzie W. Mathis, Matthias Bethge. DeepLabCut: markerless pose estimation of 
user-defined body parts with deep learning. In Nature Neuroscience, 21, 1281–1289
(2018).
2. Chengqi Lyu, Wenwei Zhang, Haian Huang, Yue Zhou, Yudong Wang, Yanyi Liu, Shilong
Zhang, Kai Chen. RTMDet: An Empirical Study of Designing Real-Time Object Detectors. 
ArXiv, abs/2212.07784, 2022.
3. Tao Jiang, Peng Lu, Li Zhang, Ningsheng Ma, Rui Han, Chengqi Lyu, Yining Li, Kai 
Chen. RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose. ArXiv, 
abs/2303.07399, 2023.