yangjun dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829 vor 1 Jahr
..
_base_ dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829 vor 1 Jahr
README.md dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829 vor 1 Jahr
faster_rcnn_hrnetv2p_w18_1x_coco.yml dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829 vor 1 Jahr
faster_rcnn_hrnetv2p_w18_2x_coco.yml dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829 vor 1 Jahr

README.md

High-resolution networks (HRNets) for object detection

Introduction

@inproceedings{SunXLW19,
  title={Deep High-Resolution Representation Learning for Human Pose Estimation},
  author={Ke Sun and Bin Xiao and Dong Liu and Jingdong Wang},
  booktitle={CVPR},
  year={2019}
}
@article{SunZJCXLMWLW19,
  title={High-Resolution Representations for Labeling Pixels and Regions},
  author={Ke Sun and Yang Zhao and Borui Jiang and Tianheng Cheng and Bin Xiao
  and Dong Liu and Yadong Mu and Xinggang Wang and Wenyu Liu and Jingdong Wang},
  journal   = {CoRR},
  volume    = {abs/1904.04514},
  year={2019}
}

Model Zoo

Backbone Type Image/gpu Lr schd Inf time (fps) Box AP Mask AP Download Configs
HRNetV2p_W18 Faster 1 1x - 36.8 - model config
HRNetV2p_W18 Faster 1 2x - 39.0 - model config