【论文阅读】 Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification,程序员大本营,技术文章内容聚合第一站。
Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification 一、摘要 尽管有可分辨的局部特征早已被用于有效地解决person ReID问题,但是需要大量昂贵的手工标注。本文提出了一种基于patch的无监督学习框架,以便从patch而不是整幅图像中学习识别特征,即利用patch之间的相似性来学习一个有区别的...
虽然在这个过程中,近景MVS数据集DTU和中近景MVS数据集Tanks & Temples也不断被新的learning-based方法霸榜,但是没有一篇文章能够跳出MVSNet构建的算法框架去思考learning-based方法未来可能的发展方向。 随着CVPR2021会议的召开,multi-view stereo领域的一篇oral文章《PatchmatchNet: Learned Multi-View Patchmatch Stereo》...
Computer science Patch-based Ensemble Learning Scheme for Heterogeneous Face Recognition WEST VIRGINIA UNIVERSITY Arun Ross ChenCunjianThe problem of Heterogeneous Face Recognition (HFR) involves comparing and matching face images that look significantly different primarily due to variations in their ...
The Broad Learning System (BLS) is a shallow network framework that benefits from its ease of optimization and speed. It has been shown to outperform machine learning approaches while remaining competitive with deep learning. Based on the current situation of TSAD, we propose the Contrastive Patch...
Explaining predictionsDeep neural networks have shown to learn highly predictive models of video data. Due to the large number of images in individual videos, a common strategy for training is to repeatedly extract short...doi:10.1007/978-3-030-28954-6_16ChristopherJ.Anders...
具体而言,PatchmatchNet是一种以learning-based Patchmatch为主体的cascade结构,主要包括基于FPN的多尺度特征提取、嵌入在cascade结构中的learning-based Patchmatch以及spatial refinement模块(用来上采样至原图大小)。 Figure 2: PatchmatchNet的结构 3.Learning-based Patchmatch ...
1、MatchNet网络就是 siamese的双分支权重共享网络,与论文Learning to Compare Image Patches via Convolutional Neural Networks有共通之处。CNN提取图像块特征,FC学习度量特征的相似度。 2、本文指出,在测试阶段,可以将特征网络和度量网络分开进行,避免匹配图像时特征提取的重复计算。首先得到图像块的特征编码保存,之后输...
loss部分是两个contrast learning loss: 一个lossLmcLcm是instance level的softcross entropy,显然也是借鉴了cvpr18年的Unsupervised feature learning via non-parametric instance discrimination。简单来说就是设置feature bank,Wm={wmj}Ni=1Wm={wjm}i=1N,N是训练集图像数目,m应该是m=1,...Mm=1,...M(即M个...
具体而言,PatchmatchNet是一种以learning-based Patchmatch为主体的cascade结构,主要包括基于FPN的多尺度特征提取、嵌入在cascade结构中的learning-based Patchmatch以及spatial refinement模块(用来上采样至原图大小)。 Figure 2: PatchmatchNet的结构 3.Learning-based Patchmatch ...