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
| 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
VBR
VR-Folding
Drunkard's Dataset
InfiniteRep
Most implemented papers
Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains
wenbowen123/iros20-6d-pose-tracking
•
•
This work presents se(3)-TrackNet, a data-driven optimization approach for long term, 6D pose tracking.
Do Different Tracking Tasks Require Different Appearance Models?
Zhongdao/UniTrack
•
•
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.
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.
Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space
gorilla-lab-scut/ss-conv
•
•
NeurIPS 2021
In this paper, we propose a novel design of Sparse Steerable Convolution (SS-Conv) to address the shortcoming; SS-Conv greatly accelerates steerable convolution with sparse tensors, while strictly preserving the property of SE(3)-equivariance.
PoseTrack21: A Dataset for Person Search, Multi-Object Tracking and Multi-Person Pose Tracking
andoer/posetrack21
•
•
CVPR 2022
Current research evaluates person search, multi-object tracking and multi-person pose estimation as separate tasks and on different datasets although these tasks are very akin to each other and comprise similar sub-tasks, e. g. person detection or appearance-based association of detected persons.
HMD-EgoPose: Head-Mounted Display-Based Egocentric Marker-Less Tool and Hand Pose Estimation for Augmented Surgical Guidance
Further, we reveal the capacity of our HMD-EgoPose framework for performant 6DoF pose estimation on a commercially available optical see-through head-mounted display (OST-HMD) through a low-latency streaming approach.
HOI4D: A 4D Egocentric Dataset for Category-Level Human-Object Interaction
leolyliu/HOI4D-Instructions
•
•
CVPR 2022
We present HOI4D, a large-scale 4D egocentric dataset with rich annotations, to catalyze the research of category-level human-object interaction.
Keypoint-Based Category-Level Object Pose Tracking from an RGB Sequence with Uncertainty Estimation
We propose a single-stage, category-level 6-DoF pose estimation algorithm that simultaneously detects and tracks instances of objects within a known category.
Structure PLP-SLAM: Efficient Sparse Mapping and Localization using Point, Line and Plane for Monocular, RGB-D and Stereo Cameras
One of the biggest challenges in parallel tracking and mapping with a monocular camera is to keep the scale consistent when reconstructing the geometric primitives.
MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior
irlab-therapeutics/mabe_2022
•
•
We introduce MABe22, a large-scale, multi-agent video and trajectory benchmark to assess the quality of learned behavior representations.
