现有的框架总是将输入从高分辨率表征编码到低分辨率表征,如ResNet,VGG(下采样32倍,分辨率从224 -> 7),然后从低分辨率恢复到高分辨率。本文提出一种新的框架:High-Resolution Network (HRNet),旨在整个处理过程中保持高分辨率的表征。 框架对比 上图展示了从低分辨率表征恢复到高分辨率表征的框架结构。其中(a)部分为...
基于深度学习的特征表示在计算机视觉任务中通常分为两类:低分辨率表示(low-resolution representations)和高分辨率表示(high-resolution representations)。 目前有两种主要的方法来获取高分辨率表示: 从网络输出的低分辨率表示或者中间中等分辨率表示恢复高分辨率表示,从down-sampling后获取的feature map中再upsam...
文中提出了一种新的体系结构,即高分辨率网络(HRNet),它能够在整个过程中保持高分辨率的表示。第一阶段构建高分辨率子网络,后续阶段逐步添加high-to-low分辨率子网络,并行地连接多分辨率子网络。通过交换贯穿于并行多分辨率子网络的信息指导多尺度融合,并不断重复这个过程。 (1)并行地连接high-to-low分辨率子...
其他平台或 GPU 卡未经过全面测试。 二、环境 操作系统:Windows 10 显卡:1650(都是坑) 模型:High-Resoultion Net(HRNet) 三、安装依赖相关的坑 HRNet安装: 1 git clone https://github.com/leoxiaobin/deep-high-resolution-net.pytorch.git 接着就是安装依赖,作者给的是: 1 pip install -r requirements.t...
paper: Deep High-Resolution Representation Learning for Visual Recognition code: HRNet Abstract HRNet,这里用的是PAMI2020的工作,整合了human pose estimation、object detection、semantic segmentation、image classification、facial landmark detection等多个视觉任务,目前Cityscapes test的分割任务中,精度最高的是HRNetV2...
High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection. Existing state-of-the-art frameworks first encode the input image as a low-resolution representation through a subnetwork that...
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{Deep High-Resolution Representation Learning for Visual Recognition}, author={Jingdong Wang and Ke Sun and Tianheng Cheng and Borui Jiang and Chaorui Deng and Yang Zhao and Dong Liu and Yadong Mu and Mingkui Tan and Xinggang Wang and Wenyu Liu and Bin Xiao}, journal = {TPAMI} year={...
our proposed network maintains high-resolution representations through the whole process. We start from a high-resolution subnetwork as the first stage, gradually add high-to-low resolution subnetworks one by one to form more stages, and connect the mutli-resolution subnetworks in p...
This is an official pytorch implementation ofDeep High-Resolution Representation Learning for Human Pose Estimation. In this work, we are interested in the human pose estimation problem with a focus on learning reliable high-resolution representations. Most existing methodsrecover high-resolution representa...