Browse > Computer Vision > Pose Estimation > Keypoint Detection

Keypoint Detection

35 papers with code · Computer Vision
Subtask of Pose Estimation

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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Greatest papers with code

Slimmable Neural Networks

ICLR 2019 JiahuiYu/slimmable_networks

Instead of training individual networks with different width configurations, we train a shared network with switchable batch normalization.

INSTANCE SEGMENTATION KEYPOINT DETECTION OBJECT DETECTION SEMANTIC SEGMENTATION

PifPaf: Composite Fields for Human Pose Estimation

CVPR 2019 vita-epfl/openpifpaf

We propose a new bottom-up method for multi-person 2D human pose estimation that is particularly well suited for urban mobility such as self-driving cars and delivery robots.

KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION SELF-DRIVING CARS

Deep Alignment Network: A convolutional neural network for robust face alignment

6 Jun 2017MarekKowalski/DeepAlignmentNetwork

Our method uses entire face images at all stages, contrary to the recently proposed face alignment methods that rely on local patches.

#7 best model for Face Alignment on 300W

FACE ALIGNMENT KEYPOINT DETECTION ROBUST FACE ALIGNMENT

MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network

ECCV 2018 salihkaragoz/pose-residual-network-pytorch

In this paper, we present MultiPoseNet, a novel bottom-up multi-person pose estimation architecture that combines a multi-task model with a novel assignment method.

HUMAN DETECTION KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION

Rethinking on Multi-Stage Networks for Human Pose Estimation

1 Jan 2019megvii-detection/MSPN

Existing pose estimation approaches fall into two categories: single-stage and multi-stage methods.

KEYPOINT DETECTION

PoseFix: Model-agnostic General Human Pose Refinement Network

CVPR 2019 mks0601/PoseFix_RELEASE

In this paper, we propose a human pose refinement network that estimates a refined pose from a tuple of an input image and input pose.

 SOTA for Multi-Person Pose Estimation on COCO (Validation AP metric )

KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION

CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark

CVPR 2019 Jeff-sjtu/CrowdPose

In this paper, we propose a novel and efficient method to tackle the problem of pose estimation in the crowd and a new dataset to better evaluate algorithms.

KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION

Distribution-Aware Coordinate Representation for Human Pose Estimation

14 Oct 2019ilovepose/DarkPose

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.

 SOTA for Pose Estimation on COCO (using extra training data)

KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION

R2D2: Reliable and Repeatable Detector and Descriptor

NeurIPS 2019 naver/r2d2

We thus propose to jointly learn keypoint detection and description together with a predictor of the local descriptor discriminativeness.

ATARI GAMES INTEREST POINT DETECTION KEYPOINT DETECTION METRIC LEARNING

Efficient adaptive non-maximal suppression algorithms for homogeneous spatial keypoint distribution

Pattern Recognition Letters 2018 BAILOOL/ANMS-Codes

Keypoint detection usually results in a large number of keypoints which are mostly clustered, redundant, and noisy.

KEYPOINT DETECTION