Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h).

2022年6月13日 · 这篇文章中的 HRNet （High-Resolution Net）是针对2D人体姿态估计（Human Pose Estimation或Keypoint Detection）任务提出的，并且该网络主要是针对单一个体的姿态评 …

Our HRNet has been applied to a wide range of vision tasks, such as image classification, objection detection, semantic segmentation and facial landmark. This is an official pytorch …

2019年8月20日 · Instead, our proposed network, named as High-Resolution Network (HRNet), maintains high-resolution representations through the whole process. There are two key …

2022年7月12日 · 在 计算机视觉 领域中，一张图像的语义信息通俗的理解就是该图像中包含的人类能定义的一些特征，比如该图像的纹理，颜色，以及图像中目标的眼睛、鼻子、类别、性别， …

而HRNet通过并行多个分辨率的分支，加上不断进行不同分支之间的信息交互，同时达到强语义信息和精准位置信息的目的。 recover high resolution. maintain high resolution. 思路在当时来 …

This is the official code of HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation. Bottom-up human pose estimation methods have difficulties in …

2020年4月1日 · We show the superiority of the proposed HRNet in a wide range of applications, including human pose estimation, semantic segmentation, and object detection, suggesting …

HRNet是微软亚洲研究院的 王井东 老师领导的团队完成的，打通图像分类、图像分割、目标检测、人脸对齐、姿态识别、风格迁移、Image Inpainting、超分、optical flow、Depth estimation …

2024年4月25日 · Hence, this paper constructs a network model, named MS-HRNet (Multi-Scale High-Resolution Network), for human pose estimation. Specifically, we propose a more …