3D Human Pose Tracking

4 papers with code • 1 benchmarks • 4 datasets

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Most implemented papers

Iterative Greedy Matching for 3D Human Pose Tracking from Multiple Views

jutanke/mv3dpose 24 Jan 2021

In this work we propose an approach for estimating 3D human poses of multiple people from a set of calibrated cameras.

Part-Aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking

ivclab/Part-Aware_Measurement_for_3D_Pose_Estimation_and_Tracking 22 Jun 2021

This paper introduces an approach for multi-human 3D pose estimation and tracking based on calibrated multi-view.

Event-based Human Pose Tracking by Spiking Spatiotemporal Transformer

jimmyzou/humanposetracking_snn 16 Mar 2023

Motivated by the above mentioned issues, we present in this paper a dedicated end-to-end sparse deep learning approach for event-based pose tracking: 1) to our knowledge this is the first time that 3D human pose tracking is obtained from events only, thus eliminating the need of accessing to any frame-based images as part of input; 2) our approach is based entirely upon the framework of Spiking Neural Networks (SNNs), which consists of Spike-Element-Wise (SEW) ResNet and a novel Spiking Spatiotemporal Transformer; 3) a large-scale synthetic dataset is constructed that features a broad and diverse set of annotated 3D human motions, as well as longer hours of event stream data, named SynEventHPD.

Uncertainty-aware State Space Transformer for Egocentric 3D Hand Trajectory Forecasting

oppo-us-research/USST ICCV 2023

In this paper, we set up an egocentric 3D hand trajectory forecasting task that aims to predict hand trajectories in a 3D space from early observed RGB videos in a first-person view.