About

Keypoint detection involves simultaneously detecting people and localizing their keypoints. Keypoints are the same thing as interest points. They are spatial locations, or points in the image that define what is interesting or what stand out in the image. They are invariant to image rotation, shrinkage, translation, distortion, and so on.

( Image credit: PifPaf: Composite Fields for Human Pose Estimation; "Learning to surf" by fotologic, license: CC-BY-2.0 )

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Libraries

Datasets

Greatest papers with code

Objects as Points

16 Apr 2019tensorflow/models

We model an object as a single point --- the center point of its bounding box.

Ranked #13 on Real-Time Object Detection on COCO (using extra training data)

KEYPOINT DETECTION REAL-TIME OBJECT DETECTION

Data Distillation: Towards Omni-Supervised Learning

CVPR 2018 facebookresearch/detectron

We investigate omni-supervised learning, a special regime of semi-supervised learning in which the learner exploits all available labeled data plus internet-scale sources of unlabeled data.

KEYPOINT DETECTION OBJECT DETECTION

Non-local Neural Networks

CVPR 2018 facebookresearch/detectron

Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time.

Ranked #8 on Keypoint Detection on COCO (Validation AP metric)

ACTION CLASSIFICATION ACTION RECOGNITION INSTANCE SEGMENTATION KEYPOINT DETECTION OBJECT DETECTION

OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

18 Dec 2018CMU-Perceptual-Computing-Lab/openpose

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

KEYPOINT DETECTION

RMPE: Regional Multi-person Pose Estimation

ICCV 2017 MVIG-SJTU/AlphaPose

In this paper, we propose a novel regional multi-person pose estimation (RMPE) framework to facilitate pose estimation in the presence of inaccurate human bounding boxes.

2D HUMAN POSE ESTIMATION HUMAN DETECTION KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION

Distribution-Aware Coordinate Representation for Human Pose Estimation

CVPR 2020 leoxiaobin/deep-high-resolution-net.pytorch

Interestingly, we found that the process of decoding the predicted heatmaps into the final joint coordinates in the original image space is surprisingly significant for human pose estimation performance, which nevertheless was not recognised before.

 Ranked #1 on Multi-Person Pose Estimation on COCO (using extra training data)

KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION

Deep High-Resolution Representation Learning for Human Pose Estimation

CVPR 2019 leoxiaobin/deep-high-resolution-net.pytorch

We start from a high-resolution subnetwork as the first stage, gradually add high-to-low resolution subnetworks one by one to form more stages, and connect the mutli-resolution subnetworks in parallel.

INSTANCE SEGMENTATION KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION OBJECT DETECTION POSE TRACKING REPRESENTATION LEARNING