Multi-Person Pose Estimation and Tracking
2 papers with code • 1 benchmarks • 1 datasets
Joint multi-person pose estimation and tracking following the PoseTrack benchmark. https://posetrack.net/
( Image credit: PoseTrack )
Benchmarks
These leaderboards are used to track progress in Multi-Person Pose Estimation and Tracking
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PoseTrack
Latest papers with no code
Texture-Based Input Feature Selection for Action Recognition
To improve the model robustness, we propose a novel method to determine the task-irrelevant content in inputs which increases the domain discrepancy.
JRDB-Pose: A Large-scale Dataset for Multi-Person Pose Estimation and Tracking
In crowded human scenes with close-up human-robot interaction and robot navigation, a deep understanding requires reasoning about human motion and body dynamics over time with human body pose estimation and tracking.
Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking
In this paper, we propose a novel online approach to learning the pose dynamics, which are independent of pose detections in current fame, and hence may serve as a robust estimation even in challenging scenarios including occlusion.
Self-supervised Keypoint Correspondences for Multi-Person Pose Estimation and Tracking in Videos
Instead of training the network for estimating keypoint correspondences on video data, it is trained on a large scale image datasets for human pose estimation using self-supervision.
FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks
Given the results of MTN, we adopt an occlusion-aware Re-ID feature strategy in the pose tracking module, where pose information is utilized to infer the occlusion state to make better use of Re-ID feature.
Multi-person Articulated Tracking with Spatial and Temporal Embeddings
Our framework consists of two main components,~\ie~SpatialNet and TemporalNet.
Multi-Domain Pose Network for Multi-Person Pose Estimation and Tracking
Multi-person human pose estimation and tracking in the wild is important and challenging.
Learning to Refine Human Pose Estimation
Multi-person pose estimation in images and videos is an important yet challenging task with many applications.
