Deep learning-based human pose estimation: A survey

C Zheng, W Wu, C Chen, T Yang, S Zhu, J Shen… - ACM Computing …, 2023 - dl.acm.org
Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

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

A Mathis, P Mamidanna, KM Cury, T Abe… - Nature …, 2018 - nature.com
Quantifying behavior is crucial for many applications in neuroscience. Videography provides
easy methods for the observation and recording of animal behavior in diverse settings, yet …

Realtime multi-person 2d pose estimation using part affinity fields

Z Cao, T Simon, SE Wei… - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
We present an approach to efficiently detect the 2D pose of multiple people in an image. The
approach uses a nonparametric representation, which we refer to as Part Affinity Fields …

Rmpe: Regional multi-person pose estimation

HS Fang, S **
A Newell, Z Huang, J Deng - Advances in neural …, 2017 - proceedings.neurips.cc
We introduce associative embedding, a novel method for supervising convolutional neural
networks for the task of detection and grou**. A number of computer vision problems can …

Towards accurate multi-person pose estimation in the wild

G Papandreou, T Zhu, N Kanazawa… - Proceedings of the …, 2017 - openaccess.thecvf.com
We propose a method for multi-person detection and 2-D pose estimation that achieves
state-of-art results on the challenging COCO keypoints task. It is a simple, yet powerful, top …

Personlab: Person pose estimation and instance segmentation with a bottom-up, part-based, geometric embedding model

G Papandreou, T Zhu, LC Chen… - Proceedings of the …, 2018 - openaccess.thecvf.com
We present a box-free bottom-up approach for the tasks of pose estimation and instance
segmentation of people in multi-person images using an efficient single-shot model. The …