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Greatest papers with code

Convolutional Pose Machines

CVPR 2016 CMU-Perceptual-Computing-Lab/openpose

Pose Machines provide a sequential prediction framework for learning rich implicit spatial models.

3D HUMAN POSE ESTIMATION STRUCTURED PREDICTION

XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera

1 Jul 2019rwightman/pytorch-image-models

The first stage is a convolutional neural network (CNN) that estimates 2D and 3D pose features along with identity assignments for all visible joints of all individuals. We contribute a new architecture for this CNN, called SelecSLS Net, that uses novel selective long and short range skip connections to improve the information flow allowing for a drastically faster network without compromising accuracy.

MONOCULAR 3D HUMAN POSE ESTIMATION MOTION CAPTURE

PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization

CVPR 2020 facebookresearch/pifuhd

Although current approaches have demonstrated the potential in real world settings, they still fail to produce reconstructions with the level of detail often present in the input images.

3D HUMAN POSE ESTIMATION 3D OBJECT RECONSTRUCTION FROM A SINGLE IMAGE 3D SHAPE RECONSTRUCTION

End-to-end Recovery of Human Shape and Pose

CVPR 2018 akanazawa/hmr

The main objective is to minimize the reprojection loss of keypoints, which allow our model to be trained using images in-the-wild that only have ground truth 2D annotations.

MONOCULAR 3D HUMAN POSE ESTIMATION WEAKLY-SUPERVISED 3D HUMAN POSE ESTIMATION

A simple yet effective baseline for 3d human pose estimation

ICCV 2017 una-dinosauria/3d-pose-baseline

Following the success of deep convolutional networks, state-of-the-art methods for 3d human pose estimation have focused on deep end-to-end systems that predict 3d joint locations given raw image pixels.

3D POSE ESTIMATION MONOCULAR 3D HUMAN POSE ESTIMATION

PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization

ICCV 2019 shunsukesaito/PIFu

We introduce Pixel-aligned Implicit Function (PIFu), a highly effective implicit representation that locally aligns pixels of 2D images with the global context of their corresponding 3D object.

3D HUMAN POSE ESTIMATION 3D OBJECT RECONSTRUCTION FROM A SINGLE IMAGE 3D SHAPE RECONSTRUCTION FROM A SINGLE 2D IMAGE

Expressive Body Capture: 3D Hands, Face, and Body from a Single Image

CVPR 2019 vchoutas/smplify-x

We use the new method, SMPLify-X, to fit SMPL-X to both controlled images and images in the wild.

3D HUMAN POSE ESTIMATION 3D RECONSTRUCTION 4