Pose Tracking
62 papers with code • 3 benchmarks • 10 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
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Libraries
Use these libraries to find Pose Tracking models and implementationsDatasets
PoseTrack
10,000 People - Human Pose Recognition Data
HOI4D
VBR
VR-Folding
Drunkard's Dataset
InfiniteRep
Latest papers
ROFT: Real-Time Optical Flow-Aided 6D Object Pose and Velocity Tracking
In this work, we introduce ROFT, a Kalman filtering approach for 6D object pose and velocity tracking from a stream of RGB-D images.
SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World
Finally, we use a pre-rendered sparse viewpoint model to create a joint posterior probability for the object pose.
BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models
Most prior efforts, however, often assume that the target object's CAD model, at least at a category-level, is available for offline training or during online template matching.
Do Different Tracking Tasks Require Different Appearance Models?
Zhongdao/UniTrack
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NeurIPS 2021
We show how most tracking tasks can be solved within this framework, and that the same appearance model can be successfully used to obtain results that are competitive against specialised methods for most of the tasks considered.
Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains
wenbowen123/iros20-6d-pose-tracking
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This work presents se(3)-TrackNet, a data-driven optimization approach for long term, 6D pose tracking.
Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning
steve-tod/stfc3
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Previous cycle-consistency correspondence learning methods usually leverage image patches for training.
POSE-ID-on—A Novel Framework for Artwork Pose Clustering
In this work, we focus our attention on the similarity among works of art based on human poses and the actions they represent, moving from the concept of Pathosformel in Aby Warburg.
CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds
HalfSummer11/CAPTRA
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ICCV 2021
For the first time, we propose a unified framework that can handle 9DoF pose tracking for novel rigid object instances as well as per-part pose tracking for articulated objects from known categories.
Iterative Greedy Matching for 3D Human Pose Tracking from Multiple Views
In this work we propose an approach for estimating 3D human poses of multiple people from a set of calibrated cameras.
Temporally Guided Articulated Hand Pose Tracking in Surgical Videos
MichiganCOG/Surgical_Hands_RELEASE
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Additionally, we collect the first dataset, Surgical Hands, that provides multi-instance articulated hand pose annotations for in-vivo videos.
