atlas

Research map / 3D vision / Human pose estimation

CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild

CVPR 2021 · 3D vision › Human pose estimation · approach: Monocular 2D-to-3D pose lifting · 113 citations (OpenAlex)

Check your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add the static-camera consistency constraintCanonPose · Human3.6MMPJPE: 81.9 -> 74.3Helped
Add the static-camera consistency constraintCanonPose · MPI-INF-3DHPPCK: 69.0 -> 77.0Helped
Use only the first two or three cameras instead of all four (ablation)CanonPose · Human3.6MMPJPE: 81.9 -> 82.7; 81.9 -> 82.0Hurt
Add joint confidences to the input and reprojection loss (ablation)CanonPose · Human3.6MMPJPE: 95.6 -> 81.9; gain of 19.4mm in MPJPEHelped
Add joint confidences to the input and reprojection loss (ablation)CanonPose · Human3.6MPMPJPE: 65.0 -> 53.0; gain of 11.2mm in PMPJPEHelped
Use ground-truth 2D annotations instead of detected 2D poses (ablation)CanonPose · Human3.6MMPJPE: 81.9 -> 65.9Helped
Replace mixed-view reprojection consistency with direct pose equality (ablation)CanonPose · Human3.6MMPJPE: 81.9 -> 554.3Hurt
Replace mixed-view reprojection consistency with direct camera equality (ablation)CanonPose · Human3.6MMPJPE: 617.9Hurt

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy