2D pose estimationSurgical instrumentsConvolutional neural networksFor many practical problems and applications, it is not feasible to create a vast and accurately labeled dataset, which restricts the application of deep learning in many areas. Semi-supervised learning algorithms intend to improve ...
Code for my paper Boosting Semi-Supervised 2D Human Pose Estimation by Revisiting Data Augmentation and Consistency Training [arxiv 2024.02] [Arxiv Link] | [Released Models] ● Abstract The 2D human pose estimation is a basic visual problem. However, supervised learning of a model requires massiv...
2.2 Semi-supervised approach 利用现有的2D keypoints detector 和back-projection module将未标注的video产生的loss计算到总loss中, 以便加强监督学习. 作者将这一问题看成是一个自编码器问题: 即利用encoder(pose estimator)将2D Pose坐标转换为3D Pose 坐标, 而decoder则是将3D Pose坐标投影到2D Pose坐标. 在具...
这个技术的理解难点在于将3D姿势反向投影回2D,因为由VideoPose3D模型预测出来的3D关键点仅仅是各个关节的相对位置,而不包含当前世界场景下的绝对位置(也就是说,你不知道人物在视频中的移动轨迹),所以如果想要将3D关键点反向投影回2D的话,必须要获得人物的身体中心(或者原点)的移动轨迹,然后再将3D关键点投影上去。为此...
An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation. [pdf] Rongchang Xie, Chunyu Wang, Wenjun Zeng, Yizhou Wang. ICCV 2021 Semi-Supervised Visual Representation Learning for Fashion Compatibility. [pdf] Ambareesh Revanur, Vijay Kumar, Deepthi Sharma ACM RecSy...
Stacked graph bone region U-net with bone representation for hand pose estimation and semi-supervised training 3D hand estimation from 2D joint information is an essential task in human-machine interaction, which has achieved great progress as an application of deep... Z Zheng,Z Hu,H Qin,......
One motivation for studying semi-supervised techniques for human pose estimation is to compensate for the lack of variety in curated 3D human pose datasets by combining labeled 3D pose data with readily available unlabeled video data—effectively, leveraging the annotations of the former and the rich...
Self-Supervised Domain Adaptation for Patient-Specific, Real-Time Tissue Tracking Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose Estimation Simulation of Brain Resection for Cavity Segmentation Using Self-Supervised and SemiSupervised Learning Self-Supervised Discovery of Anatomical...
Semi-supervised learning is a significant approach to learn robust human pose estimation models that perform well on wild images. Existing semi-supervised ... Haixin Wang,Lu Zhou,Yingying Chen,... - Machine Intelligence Research 被引量: 0发表: 2024年 Semi-supervised machine learning approach for...
Because semi-supervised learning requires less human effort and gives higher accuracy, it is of great interest both in theory and in practice.How many semi-supervised learning methods are there?Many. Some often-used methods include: EM with generative mixture models, self-training, consistency ...