本文简要介绍论文“VimTS: A Unified Video and Image Text Spotter for Enhancing the Cross-domain Generalization”的主要工作。文本端到端识别是一项从图像或视频序列中提取文本信息的任务,它面临着图像到图像和图像到视频泛化等跨域自适应的挑战。在本文中,我们引入了一种新的方法,称为VimTS,它通过实现不同任务...
论文名称:Self-Challenging Improves Cross-Domain Generalization 论文地址:arxiv.org/pdf/2007.0245 代码地址:github.com/DeLightCMU/R 写在前面 本科时看的第一篇文章就是domain adaptation相关,当时就看的一脸懵逼,这次再接触到domain generation方向的文章感觉好理解多了(虽然还有大段的证明看不懂)。回过头来想想本...
We introduce a simple training heuristic, Representation Self-Challenging (RSC), that significantly improves the generalization of CNN to the out-of-domain data. RSC iteratively challenges (discards) the dominant features activated on the training data, and forces the network to activate remaining ...
为了解决这个问题,研究者们提出了多种跨域学习方法,如域适应(Domain Adaptation)和域泛化(Domain Generalization)等。 域适应方法旨在减少源域和目标域之间的分布差异,从而使在源域上学到的模型能够更好地适应目标域。域适应方法通常包括特征空间对齐、样本重加权和域不变特征学习等技术。例如...
We introduce a simple training heuristic, Representation Self-Challenging (RSC), that significantly improves the generalization of CNN to the out-of-domain data. RSC iteratively challenges (discards) the dominant features activated on the training data, and forces the network to activate remaining ...
论文阅读:ECCV 2020 | Self-Challenging Improves Cross-Domain Generalization,程序员大本营,技术文章内容聚合第一站。
The benchmark collection in the paper is releasing and you can access it at here. 🎉🎉🎉 CrossEarth is the first VFM for Remote Sensing Domain Generalization (RSDG) semantic segmentation. We just release the arxiv paper of CrossEarth. You can access CrossEarth at here.📑...
This is the official implementation of Self-Challenging Improves Cross-Domain Generalization, ECCV2020 - DeLightCMU/RSC
, UK 3University of Surrey, UK {guoyurong, duruoyi, yuandong, mazhanyu}@bupt.edu.cn, t.hospedales@ed.ac.uk, y.song@surrey.ac.uk Abstract Although existing few-shot learning works yield promis- ing results for in-domain queries, they still suffer from weak...
Self-challenging improves cross-domain generalization Graph optimal transport for cross-domain alignment Cross-domain detection via graph-induced prototype alignment Cross-domain correspondence learning for exemplar-based image translation Cross-domain object detection through coarse-to-fine feature adaptation ...