Pose Estimation
1366 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
JHMDB
PASCAL3D+
LSP
300W
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
Most implemented papers
PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data
In comparison with person re-identification (ReID), which has been widely studied in the research community, vehicle ReID has received less attention.
DETRs with Hybrid Matching
HDETR/H-Deformable-DETR
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CVPR 2023
One-to-one set matching is a key design for DETR to establish its end-to-end capability, so that object detection does not require a hand-crafted NMS (non-maximum suppression) to remove duplicate detections.
DeepPose: Human Pose Estimation via Deep Neural Networks
open-mmlab/mmpose
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CVPR 2014
We propose a method for human pose estimation based on Deep Neural Networks (DNNs).
Rethinking on Multi-Stage Networks for Human Pose Estimation
Existing pose estimation approaches fall into two categories: single-stage and multi-stage methods.
Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation
hughw19/NOCS_CVPR2019
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CVPR 2019
The goal of this paper is to estimate the 6D pose and dimensions of unseen object instances in an RGB-D image.
Improvements to Target-Based 3D LiDAR to Camera Calibration
The homogeneous transformation between a LiDAR and monocular camera is required for sensor fusion tasks, such as SLAM.
BlazePose: On-device Real-time Body Pose tracking
google/mediapipe
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We present BlazePose, a lightweight convolutional neural network architecture for human pose estimation that is tailored for real-time inference on mobile devices.
UniFormer: Unifying Convolution and Self-attention for Visual Recognition
Different from the typical transformer blocks, the relation aggregators in our UniFormer block are equipped with local and global token affinity respectively in shallow and deep layers, allowing to tackle both redundancy and dependency for efficient and effective representation learning.
AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time
Accurate whole-body multi-person pose estimation and tracking is an important yet challenging topic in computer vision.
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach
xingyizhou/pose-hg-3d
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ICCV 2017
We propose a weakly-supervised transfer learning method that uses mixed 2D and 3D labels in a unified deep neutral network that presents two-stage cascaded structure.
