Pose Tracking
60 papers with code • 3 benchmarks • 9 datasets
Pose Tracking is the task of estimating multi-person human poses in videos and assigning unique instance IDs for each keypoint across frames. Accurate estimation of human keypoint-trajectories is useful for human action recognition, human interaction understanding, motion capture and animation.
Source: LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking
Benchmarks
These leaderboards are used to track progress in Pose Tracking
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
Libraries
Use these libraries to find Pose Tracking models and implementationsDatasets
PoseTrack
10,000 People - Human Pose Recognition Data
HOI4D
VR-Folding
Drunkard's Dataset
InfiniteRep
Most implemented papers
Deep High-Resolution Representation Learning for Human Pose Estimation
leoxiaobin/deep-high-resolution-net.pytorch
•
•
CVPR 2019
We start from a high-resolution subnetwork as the first stage, gradually add high-to-low resolution subnetworks one by one to form more stages, and connect the mutli-resolution subnetworks in parallel.
Simple Baselines for Human Pose Estimation and Tracking
leoxiaobin/pose.pytorch
•
•
ECCV 2018
There has been significant progress on pose estimation and increasing interests on pose tracking in recent years.
BlazePose: On-device Real-time Body Pose tracking
google/mediapipe
•
•
We present BlazePose, a lightweight convolutional neural network architecture for human pose estimation that is tailored for real-time inference on mobile devices.
Event-based Camera Pose Tracking using a Generative Event Model
Event-based vision sensors mimic the operation of biological retina and they represent a major paradigm shift from traditional cameras.
PoseTrack: Joint Multi-Person Pose Estimation and Tracking
In this work, we introduce the challenging problem of joint multi-person pose estimation and tracking of an unknown number of persons in unconstrained videos.
Capturing Hand Motion with an RGB-D Sensor, Fusing a Generative Model with Salient Points
In this work, we propose a framework for hand tracking that can capture the motion of two interacting hands using only a single, inexpensive RGB-D camera.
PoseTrack: A Benchmark for Human Pose Estimation and Tracking
open-mmlab/mmpose
•
•
CVPR 2018
In this work, we aim to further advance the state of the art by establishing "PoseTrack", a new large-scale benchmark for video-based human pose estimation and articulated tracking, and bringing together the community of researchers working on visual human analysis.
Multigrid Predictive Filter Flow for Unsupervised Learning on Videos
aimerykong/predictive-filter-flow
•
•
We introduce multigrid Predictive Filter Flow (mgPFF), a framework for unsupervised learning on videos.
LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking
To the best of our knowledge, this is the first paper to propose an online human pose tracking framework in a top-down fashion.
6-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints
j96w/6-PACK
•
•
We present 6-PACK, a deep learning approach to category-level 6D object pose tracking on RGB-D data.
