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...
The performance is nonetheless unmet when tested on samples from different distributions, leading to the challenges in cross-domain image classification. We introduce a simple training heuristic, Representation Self-Challenging (RSC), that significantly improves the generalization of CNN to the out-of-...
The performance is nonetheless unmet when tested on samples from different distributions, leading to the challenges in cross-domain image classification. We introduce a simple training heuristic, Representation Self-Challenging (RSC), that significantly improves the generalization of CNN to the out-of-...
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。
我们通过提高模型的泛化能力来解决这个cross-domain few-shot learning(CDFSL)问题。具体来说,我们在模型用noise-enhanced supervised autoencoder(NSAE)来捕获更广泛的特征分布的变化。 1. Methodology 1.1. Preliminaries# Problem formulation:源数据集有一个大规模的标记数据集Ds,而目标数据集只有有限的标记图像。我们...
This is the official implementation of Self-Challenging Improves Cross-Domain Generalization, ECCV2020 - DeLightCMU/RSC
In contrast to the domain adaptation frameworks, domain generalization methods aim at generalizing from a set of seen domains to the unseen domain without accessing instances from the unseen domain during the training stage 与域自适应框架相比,域泛化方法的目的是将从一组可见域泛化到未见域,而不在训练...
In this paper, we compare three different generalization methods for in-domain and cross-domain opinion holder extraction being simple unsupervised word clustering, an induction method inspired by distant supervision and the usage of lexical resources. The generalization methods are incorporated into divers...
A broader study ofcross-domain few-shot learning Transferring cross-domain knowledge for video sign language recognition Classes matter: A fine-grained adversarial approach to cross-domain semantic segmentation On the limits of cross-domain generalization in automated X-ray prediction ...