融合:将变换后的faeture map相加 Representation Head 如图4所示,对应不同任务,作者设计了不同的表征头,并且分别命名为HRNetV1,HRNetV2,HRNetV2p。 HRNetV1:如(a)所示,仅仅输出高分辨率的特征。用于人体姿态估计任务。 HRNetV2:如(b)所示,将低分辨率的表征通过双线性上采样,然后将4个表征concat。用于语义分割任务。
在 COCO test-dev 数据集上,HRNetV1 和现有最方法进行比较,在精度、Params和GFLOP方面有更大的提升。 image.png 在语义分割和目标检测的结果评估不作探究。 消融实验 1.不同分辨率的特征图 训练两个 HRNetV1 网络,HRNetV1-W32 进行人体姿势估计,使用 HRNetV2-W48 进行语义分割。
一直是懒,然后代码太长,分析代码真的要有决心+耐心+毅力,不然的话很容易放弃的,一件事情你做了百分之99就等同于没有做,行百里者半九十,就是这个道理,希望所有在这个领域内的小白通过阅读文献,编写代码来提升自己,相信你自己,你挺棒的。
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...
out += residual out = self.relu(out) return out 3 程序结果 参考: 7Deep High-Resolution Representation Learning for Human Pose Estimation 论文地址: http://xxx.itp.ac.cn/pdf/1904.04514.pdfxxx.itp.ac.cn/pdf/1904.04514.pdf 代码地址:...
The display of line graphics such as design drawings or land registry maps on a television monitor is considerably improved compared with known methods by the fact that the graphics for display are prepared in a black-white bit matrix which is much finer, preferably 4 x 4 times finer, than ...
论文链接:Deep High-Resolution Representation Learning for Human Pose Estimation 时间:2019.02 CVPR2019 作者团队:Ke Sun Bin Xiao Dong Liu Jingdong Wang 分类:计算机视觉--人体关键点检测--2D top-down 目录: 1.HRNet背景 2.HRNet姿态识别 3.HRNet网络架构图 ...
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...
{Bin.Xiao,jingdw}@microsoftAbstractHigh-resolutionrepresentationlearningplaysanessen-tialroleinmanyvisionproblems,e.g.,poseestimationandsemanticsegmentation.Thehigh-resolutionnetwork(HRNet)[91],recentlydevelopedforhumanposeestima-tion,maintainshigh-resolutionrepresentationsthroughthewholeprocessbyconnectinghigh-to-low...
Deep High-Resolution Representation Learning for Human Pose Estimation Ke Sun, Bin Xiao, Dong Liu, Jingdong Wang CVPR 2019|February 2019 Published by IEEE DOI Download BibTex In this paper, we are interested in the human pose estimation problem with a focus on learning reliable ...