Keypoint Detection

74 papers with code • 7 benchmarks • 5 datasets

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 )

Greatest papers with code

Simple Baselines for Human Pose Estimation and Tracking

Microsoft/human-pose-estimation.pytorch ECCV 2018

There has been significant progress on pose estimation and increasing interests on pose tracking in recent years.

Keypoint Detection Pose Tracking

Improving Convolutional Networks With Self-Calibrated Convolutions

osmr/imgclsmob CVPR 2020

Recent advances on CNNs are mostly devoted to designing more complex architectures to enhance their representation learning capacity.

Instance Segmentation Keypoint Detection +3

DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model

DeepLabCut/DeepLabCut 10 May 2016

The goal of this paper is to advance the state-of-the-art of articulated pose estimation in scenes with multiple people.

Keypoint Detection Multi-Person Pose Estimation

Associative Embedding: End-to-End Learning for Joint Detection and Grouping

open-mmlab/mmpose NeurIPS 2017

We introduce associative embedding, a novel method for supervising convolutional neural networks for the task of detection and grouping.

Instance Segmentation Keypoint Detection +1

Regressive Domain Adaptation for Unsupervised Keypoint Detection

thuml/Transfer-Learning-Library 10 Mar 2021

First, based on our observation that the probability density of the output space is sparse, we introduce a spatial probability distribution to describe this sparsity and then use it to guide the learning of the adversarial regressor.

Domain Adaptation Keypoint Detection

Rethinking on Multi-Stage Networks for Human Pose Estimation

chenyilun95/tf-cpn 1 Jan 2019

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

Keypoint Detection

Cascaded Pyramid Network for Multi-Person Pose Estimation

chenyilun95/tf-cpn CVPR 2018

In this paper, we present a novel network structure called Cascaded Pyramid Network (CPN) which targets to relieve the problem from these "hard" keypoints.

Keypoint Detection Multi-Person Pose Estimation

Slimmable Neural Networks

JiahuiYu/slimmable_networks ICLR 2019

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

Instance Segmentation Keypoint Detection +2

OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association

vita-epfl/openpifpaf 3 Mar 2021

We present a generic neural network architecture that uses Composite Fields to detect and construct a spatio-temporal pose which is a single, connected graph whose nodes are the semantic keypoints (e. g., a person's body joints) in multiple frames.

Keypoint Detection Multi-Person Pose Estimation +1