Command Palette
Search for a command to run...
4 months ago
An Integral Pose Regression System for the ECCV2018 PoseTrack Challenge
Xiao Sun; Chuankang Li; Stephen Lin

Abstract
For the ECCV 2018 PoseTrack Challenge, we present a 3D human pose estimation system based mainly on the integral human pose regression method. We show a comprehensive ablation study to examine the key performance factors of the proposed system. Our system obtains 47mm MPJPE on the CHALL_H80K test dataset, placing second in the ECCV2018 3D human pose estimation challenge. Code will be released to facilitate future work.
Code Repositories
JimmySuen/integral-human-pose
Official
pytorch
Mentioned in GitHub
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| 3d-human-pose-estimation-on-chall-h80k | ResNet | MPJPE: 55.3 |
Build AI with AI
From idea to launch — accelerate your AI development with free AI co-coding, out-of-the-box environment and best price of GPUs.
AI Co-coding
Ready-to-use GPUs
Best Pricing
Hyper Newsletters
Subscribe to our latest updates
We will deliver the latest updates of the week to your inbox at nine o'clock every Monday morning
Powered by MailChimp