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
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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
Latest papers
BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects
NVlabs/BundleSDF
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CVPR 2023
We present a near real-time method for 6-DoF tracking of an unknown object from a monocular RGBD video sequence, while simultaneously performing neural 3D reconstruction of the object.
GarmentTracking: Category-Level Garment Pose Tracking
xiaoxiaoxh/GarmentTracking
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CVPR 2023
In this work, we present a complete package to address the category-level garment pose tracking task: (1) A recording system VR-Garment, with which users can manipulate virtual garment models in simulation through a VR interface.
3D-POP - An automated annotation approach to facilitate markerless 2D-3D tracking of freely moving birds with marker-based motion capture
Recent advances in machine learning and computer vision are revolutionizing the field of animal behavior by enabling researchers to track the poses and locations of freely moving animals without any marker attachment.
Event-based Human Pose Tracking by Spiking Spatiotemporal Transformer
jimmyzou/humanposetracking_snn
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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.
3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose Estimation
deepmind/threednel
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ICCV 2023
In this paper, we introduce probabilistic modeling to the inverse graphics framework to quantify uncertainty and achieve robustness in 6D pose estimation tasks.
OpenApePose: a database of annotated ape photographs for pose estimation
Because of their close relationship with humans, non-human apes (chimpanzees, bonobos, gorillas, orangutans, and gibbons, including siamangs) are of great scientific interest.
Enhancing Generalizable 6D Pose Tracking of an In-Hand Object with Tactile Sensing
When manipulating an object to accomplish complex tasks, humans rely on both vision and touch to keep track of the object's 6D pose.
Fast and Robust Video-Based Exercise Classification via Body Pose Tracking and Scalable Multivariate Time Series Classifiers
We analyze the accuracy and robustness of BodyMTS and show that it is robust to different types of noise caused by either video quality or pose estimation factors.
PixTrack: Precise 6DoF Object Pose Tracking using NeRF Templates and Feature-metric Alignment
We present PixTrack, a vision based object pose tracking framework using novel view synthesis and deep feature-metric alignment.
AvatarPoser: Articulated Full-Body Pose Tracking from Sparse Motion Sensing
In this paper, we present AvatarPoser, the first learning-based method that predicts full-body poses in world coordinates using only motion input from the user's head and hands.
