Deep co-training with task decomposition for semisupervised domain adaptation一文中,将SSDA拆解为SSL和UDA任务。两个不同的子任务分别产生伪标签,并通过协同训练相互学习。 Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation一文中通过测量成对特征相似性将目标特征分组。 Multi-level Consistency ...
论文链接:Semi-Supervised Domain Adaptation via Minimax Entropy,ICCV2019 代码链接:github.com/VisionLearni 是早期半监督学习和域适应结合的工作,主要解决如何使算法在不同数据域之间具备迁移能力的问题。这个方向个人觉得有些小众,因为在实际应用场景很少有符合定义的数据集,大部分都是unsupervised domain adaptation(UDA...
论文链接:Semi-Supervised Domain Adaptation via Minimax Entropy, 2019 ICCV 项目链接:https://cs-people.bu.edu/keisaito/research/MME.html里面有代码库 一、问题设定与背景: SSDA:半监督域适应,即有标签源域、少量有标签目标域+大量无标签目标域 问题:无标签域适应不需要来自目标域的监督,通过对齐源域和目标...
论文标题:Semi-supervised Domain Adaptation in Graph Transfer Learning论文作者:论文来源:2024 aRxiv论文地址:download 论文代码:download视屏讲解:click 1-摘要作为图转移学习的一个特殊情况,图上的无监督域自适应的目的是将知识从标签丰富的源图转移到未标记的目标图。然而,具有拓扑结构和属性的图通常具有相当大的...
Domain adaptation (DA) is a representation learning methodology that transfers knowledge from a label-sufficient source domain to a label-scarce target domain. While most of early methods are focused on unsupervised DA (UDA), several studies on semi-supervised DA (SSDA) are recently suggested. In...
DAVOS: Semi-Supervised Video Object Segmentation via Adversarial Domain Adaptation Domain shift has always been one of the primary issues in video object\nsegmentation (VOS), for which models suffer from degeneration when tested on\nunfam... J Zhang,Z Wang,S Zhang,... 被引量: 0发表: 2021年...
Semi-supervised Domain Adaptation.In the SSDA setting [41], we assume a sparse set of labelled target data\(\mathcal {D}_T\)is provided along with a large set of unlabelled target data\(\overline{\mathcal {D}}_{T}\). The goal is to learn a model that fits both the source and ...
论文链接: Multi-level Consistency Learning for Semi-supervised Domain Adaptation本文提出了一种用于 SSDA 的多级一致性学习 (MCL) 框架。具体来说,本文的 MCL 在三个级别上规范了目标域样本的不同视图的一…
Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation论文笔记 Arthur Wong Love AI & Life7 人赞同了该文章 论文链接: https://arxiv.org/abs/2104.09415v1arxiv.org/abs/2104.09415v1 在半监督域适应中,目标域中每个类别的几个标记样本引导剩余目标样本的特征围绕它们进行聚合。然而,训练...
semi-supervised adaptation where the target domain is partially labeled, and (ii) multi-domain adaptation where there could be more than one domain in sou... R Gopalan,R Li,R Chellappa - 《IEEE Transactions on Pattern Analysis & Machine Intelligence》 被引量: 103发表: 2013年 Semi-Supervise...