Keypoint Estimation
28 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Keypoint Estimation
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Libraries
Use these libraries to find Keypoint Estimation models and implementations
GRIT
Most implemented papers
Mask R-CNN
matterport/Mask_RCNN
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ICCV 2017
Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance.
Objects as Points
We model an object as a single point --- the center point of its bounding box.
SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation
lzccccc/SMOKE
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Estimating 3D orientation and translation of objects is essential for infrastructure-less autonomous navigation and driving.
FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic Instance-Aware Convolutions
We propose a fully convolutional multi-person pose estimation framework using dynamic instance-aware convolutions, termed FCPose.
Bottom-up Object Detection by Grouping Extreme and Center Points
xingyizhou/ExtremeNet
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CVPR 2019
With the advent of deep learning, object detection drifted from a bottom-up to a top-down recognition problem.
KeyPose: Multi-View 3D Labeling and Keypoint Estimation for Transparent Objects
google-research/google-research
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CVPR 2020
We address two problems: first, we establish an easy method for capturing and labeling 3D keypoints on desktop objects with an RGB camera; and second, we develop a deep neural network, called $KeyPose$, that learns to accurately predict object poses using 3D keypoints, from stereo input, and works even for transparent objects.
CenterNet3D: An Anchor Free Object Detector for Point Cloud
wangguojun2018/CenterNet3d
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However, because inherent sparsity of point clouds, 3D object center points are likely to be in empty space which makes it difficult to estimate accurate boundaries.
Whole-Body Human Pose Estimation in the Wild
This paper investigates the task of 2D human whole-body pose estimation, which aims to localize dense landmarks on the entire human body including face, hands, body, and feet.
HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation
Jeff-sjtu/HybrIK
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CVPR 2021
We show that HybrIK preserves both the accuracy of 3D pose and the realistic body structure of the parametric human model, leading to a pixel-aligned 3D body mesh and a more accurate 3D pose than the pure 3D keypoint estimation methods.
Single Image 3D Interpreter Network
In this work, we propose 3D INterpreter Network (3D-INN), an end-to-end framework which sequentially estimates 2D keypoint heatmaps and 3D object structure, trained on both real 2D-annotated images and synthetic 3D data.
