Pose Estimation
1358 papers with code • 28 benchmarks • 114 datasets
Pose Estimation is a computer vision task where the goal is to detect the position and orientation of a person or an object. Usually, this is done by predicting the location of specific keypoints like hands, head, elbows, etc. in case of Human Pose Estimation.
A common benchmark for this task is MPII Human Pose
( Image credit: Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose )
Benchmarks
These leaderboards are used to track progress in Pose Estimation
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Libraries
Use these libraries to find Pose Estimation models and implementations
MS COCO
KITTI
MPII
3DPW
AMASS
DensePose
PASCAL3D+
JHMDB
300W
LSP
Subtasks
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3D Human Pose Estimation
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Keypoint Detection
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3D Pose Estimation
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6D Pose Estimation
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6D Pose Estimation
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Hand Pose Estimation
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6D Pose Estimation using RGB
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Multi-Person Pose Estimation
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Head Pose Estimation
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Human Pose Forecasting
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Animal Pose Estimation
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6D Pose Estimation using RGBD
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Vehicle Pose Estimation
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RF-based Pose Estimation
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Car Pose Estimation
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Hand Joint Reconstruction
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Activeness Detection
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Semi-supervised 2D and 3D landmark labeling
Latest papers with no code
GISR: Geometric Initialization and Silhouette-based Refinement for Single-View Robot Pose and Configuration Estimation
For autonomous robotics applications, it is crucial that robots are able to accurately measure their potential state and perceive their environment, including other agents within it (e. g., cobots interacting with humans).
ProbRadarM3F: mmWave Radar based Human Skeletal Pose Estimation with Probability Map Guided Multi-Format Feature Fusion
However, mmWave radar relies on the collection of reflected signals from the target, and the radar signals containing information is difficult to be fully applied.
Joint Estimation of Identity Verification and Relative Pose for Partial Fingerprints
Currently, portable electronic devices are becoming more and more popular.
Pose Priors from Language Models
We present a zero-shot pose optimization method that enforces accurate physical contact constraints when estimating the 3D pose of humans.
Multi-hop graph transformer network for 3D human pose estimation
Accurate 3D human pose estimation is a challenging task due to occlusion and depth ambiguity.
Blending Distributed NeRFs with Tri-stage Robust Pose Optimization
In the third stage, we fine-tune the transformation between NeRFs by Model2Model pose optimization.
IntervenGen: Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning
Imitation learning is a promising paradigm for training robot control policies, but these policies can suffer from distribution shift, where the conditions at evaluation time differ from those in the training data.
HandSSCA: 3D Hand Mesh Reconstruction with State Space Channel Attention from RGB images
Reconstructing a hand mesh from a single RGB image is a challenging task because hands are often occluded by objects.
Sports Analysis and VR Viewing System Based on Player Tracking and Pose Estimation with Multimodal and Multiview Sensors
The visualization results showcase the immense potential of our sports visualization system on the domain of watching games on VR/AR devices.
Behavior Imitation for Manipulator Control and Grasping with Deep Reinforcement Learning
Finally, these reference motions are used to formulate a reinforcement learning problem, enabling the agent to learn a policy for imitating human arm motions.
