Unified 2D Human Pose Estimation There exist multiple datasets for 2D human pose estimation, each with its unique set of annotated body joints.Generally, each neural network is trained on a particular ...

Method: We propose PoseRL-Net, a deep learning-based pose recognition model that enhances accuracy and robustness in human pose estimation. PoseRL-Net integrates multiple components, including a ...

Sapiens introduces the first model capable of 1K resolution, natively supporting high-fidelity inference for human-centric tasks and setting new benchmarks in 2D pose estimation, body-part ...

This paper introduces the Human Pose Estimation based on the Single-Input Single-Output (SISO) Ultra-Wideband (UWB) Radar (HPSUR) benchmark, a pioneering approach in human pose estimation integrating ...

Our understanding of the neural basis of human pose perception has thus far been limited by the lack of natural image datasets representative of the enormous pose space of everyday visual experience ...

Y. Zhang et al., “3d-aware neural body fitting for occlusion robust 3d human pose estimation” in Proceedings of the IEEE/CVF International Conference on Computer Vision, Agapito,Y. Furukawa, K.

The most popular pose estimation algorithm is OpenPose (OP) (14) which uses a Convolutional Neural Network (CNN) to detect keypoints and then constructs a kinematic skeleton of the human body ...