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 with no code
MS-MANO: Enabling Hand Pose Tracking with Biomechanical Constraints
To address this, we integrate a musculoskeletal system with a learnable parametric hand model, MANO, to create a new model, MS-MANO.
You Only Scan Once: A Dynamic Scene Reconstruction Pipeline for 6-DoF Robotic Grasping of Novel Objects
In the realm of robotic grasping, achieving accurate and reliable interactions with the environment is a pivotal challenge.
Real Acoustic Fields: An Audio-Visual Room Acoustics Dataset and Benchmark
The dataset includes high-quality and densely captured room impulse response data paired with multi-view images, and precise 6DoF pose tracking data for sound emitters and listeners in the rooms.
High-Fidelity SLAM Using Gaussian Splatting with Rendering-Guided Densification and Regularized Optimization
We propose a dense RGBD SLAM system based on 3D Gaussian Splatting that provides metrically accurate pose tracking and visually realistic reconstruction.
APTv2: Benchmarking Animal Pose Estimation and Tracking with a Large-scale Dataset and Beyond
Animal Pose Estimation and Tracking (APT) is a critical task in detecting and monitoring the keypoints of animals across a series of video frames, which is essential for understanding animal behavior.
No More Shortcuts: Realizing the Potential of Temporal Self-Supervision
To address these issues, we propose 1) a more challenging reformulation of temporal self-supervision as frame-level (rather than clip-level) recognition tasks and 2) an effective augmentation strategy to mitigate shortcuts.
GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting
This strategy is essential to extend 3D Gaussian representation to reconstruct the whole scene rather than synthesize a static object in existing methods.
Improving Multi-Person Pose Tracking with A Confidence Network
Specifically, the keypoint confidence network is designed to determine whether each keypoint is occluded, and it is incorporated into the pose estimation module.
Human Pose-based Estimation, Tracking and Action Recognition with Deep Learning: A Survey
This paper presents a comprehensive survey of pose-based applications utilizing deep learning, encompassing pose estimation, pose tracking, and action recognition. Pose estimation involves the determination of human joint positions from images or image sequences.
UniQuadric: A SLAM Backend for Unknown Rigid Object 3D Tracking and Light-Weight Modeling
Subsequently, in the part of object state estimation, we propose a tightly coupled optimization model for object pose and scale estimation, incorporating hybrids constraints into a novel dual sliding window optimization framework for joint estimation.
