Pose Tracking
61 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 with no code
Multi-Modal Neural Radiance Field for Monocular Dense SLAM with a Light-Weight ToF Sensor
Specifically, we propose a multi-modal implicit scene representation that supports rendering both the signals from the RGB camera and light-weight ToF sensor which drives the optimization by comparing with the raw sensor inputs.
Learning from Synthetic Human Group Activities
The study of complex human interactions and group activities has become a focal point in human-centric computer vision.
GenPose: Generative Category-level Object Pose Estimation via Diffusion Models
Object pose estimation plays a vital role in embodied AI and computer vision, enabling intelligent agents to comprehend and interact with their surroundings.
A Gated Attention Transformer for Multi-Person Pose Tracking
Multi-person pose tracking is an important element for many applications and requires to estimate the human poses of all persons in a video and to track them over time.
Counter-Hypothetical Particle Filters for Single Object Pose Tracking
However, the particle filter is prone to particle deprivation due to the high-dimensional nature of 6D pose.
Design, Implementation and Evaluation of an External Pose-Tracking System for Underwater Cameras
In order to advance underwater computer vision and robotics from lab environments and clear water scenarios to the deep dark ocean or murky coastal waters, representative benchmarks and realistic datasets with ground truth information are required.
Event-based Camera Tracker by $\nabla$t NeRF
To enable the computation of the temporal gradient of the scene, we augment NeRF's camera pose as a time function.
Markerless 3D human pose tracking through multiple cameras and AI: Enabling high accuracy, robustness, and real-time performance
Tracking 3D human motion in real-time is crucial for numerous applications across many fields.
Human from Blur: Human Pose Tracking from Blurry Images
The key idea is to tackle the inverse problem of image deblurring by modeling the forward problem with a 3D human model, a texture map, and a sequence of poses to describe human motion.
ShaRPy: Shape Reconstruction and Hand Pose Estimation from RGB-D with Uncertainty
Therefore, we propose ShaRPy, the first RGB-D Shape Reconstruction and hand Pose tracking system, which provides uncertainty estimates of the computed pose, e. g., when a finger is hidden or its estimate is inconsistent with the observations in the input, to guide clinical decision-making.
