(5)在相同的5-way 5-shot(或5-way 1-shot)评价设置下,mini和tired数据集的测试结果明显低于DomainNet和mini→CUB数据集的测试结果。这表明域间隙(由风格转换引起)与广泛使用的现实数据集(即DomainNet和mini→CUB)相比,前两个数据集的类别差距(由FSL引起的)甚至更大,这证明了使用这两个合成数据集作为新的DA-...
论文链接:[2003.08626] Domain-Adaptive Few-Shot Learning (arxiv.org) 代码:https://github.com/dingmyu/DAPN 摘要 现有的小样本学习(FSL)方法隐式假设少数target类样本与source类样本来自同一领域。然而,在实践中,这种假设通常是无效的——target类可能来自不同的领域。 本文解决了领域自适应小样本学习(DA-FSL)...
论文地址:https://www.aminer.cn/pub/5e7495c591e0111c7cee13bb/domain-adaptive-few-shot-learning 论文解读参考:https://blog.csdn.net/m0_37929824/article/details/105379668 论文代码参考:https://github.com/dingmyu/DAPN 本篇文章只记录个人阅读论文的笔记,具体翻译、代码等不展开,详细可见上述的链接. 最...
论文阅读问题总结(六):Meta-Learning with Domain Adaption for Few-shot Learning Under Domain Shift,程序员大本营,技术文章内容聚合第一站。
Recently, few-shot learning (FSL) has exhibited remarkable performance in computer vision tasks. However, the existing FSL approaches perform poorly when facing data shortages and domain variations between the source and target datasets. This is because the target domain is hidden during training and...
Most few-shot learning works rely on the same domain assumption between the base and the target tasks, hindering their practical applications. This paper proposes an adaptive transformer network (ADAPTER), a simple but effective solution for cross-domain few-shot learning where there exist large ...
Domain Adaptive Faster R-CNN for object detection Feng Nie AI Scientist Feng Nie: Domain Adaptive Faster R-CNN for object detection in the wild 1. 概述: 这篇论文发表在CVPR2018,几乎是第一篇将无监督域适应方法应用在目标检测领域的研究。目标检测通常假定训练和测试数据是从相同的分布中提取的,然而,在...
Task-aware Adaptive Learning for Cross-domain Few-shot Learning Yurong Guo1, Ruoyi Du1, Yuan Dong1, Timothy Hospedales2, Yi-Zhe Song3, Zhanyu Ma1* 1Beijing University of Posts and Telecommunications, China 2University of Edinburgh, UK 3University of Surrey, UK...
论文题目: Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segme… 阅读全文 赞同 514 115 条评论 分享 收藏 迁移学习:域自适应理论简介Domain Adaptation Theory 江俊广 本文主要介绍域自适应(Domain Adaptation)最基本的学习理论,全文不涉及理论的证明...
《Dual Adaptive Representation Alignment for Cross-Domain Few-Shot Learning》阅读笔记 Amethyst2022 41 人赞同了该文章 目录 收起 一、论文简介 二、摘要 三、引言和动机 四、方法 4.1 原型特征对齐 4.2 归一化分布对齐 4.3 渐进式元学习框架 五、实验 六、总结&局限性 参考文献 一、论文简介 作者单位:...