Domain generalizationObject detection Attention modelDomain generalization methods in object detection aim to learn a domain-invariant detector for different domains. However, it is difficult to obtain a domain-invariant detector when there is large......
Deep Learning for Generic Object Detection: A Survey 最近,中国国防科技大学、芬兰奥卢大学、澳大利亚悉尼大学、中国香港中文大学和加拿大滑铁卢大学等人推出一篇最新目p learning object dete... 目标检测 机器学习 参考资源 DSOD: Learning Deeply Supervised Object Detectors from Scratch 复旦、清华和英特尔中国研究院...
Domain adaptation(DA: 域自适应),Domain generalization(DG: 域泛化)一直以来都是各大顶会的热门研究方向。DA假设我们有有一个带标签的训练集(源域),这时… 阅读全文 赞同 228 18 条评论 分享 收藏 Invariant Risk Minimization系列阅读笔记 ...
域适应包括四种情况：红色方框中1种，绿色方框中3种。绿色方框对应的研究为域适应。即知道目标域是什么...
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 ...
Self-Supervised CycleGAN for Object-Preserving Image-to-Image Domain Adaptation Dual Mixup Regularized Learning for Adversarial Domain Adaptation Mind the Discriminability: Asymmetric Adversarial Domain Adaptation 域泛化(domain generalization): Self-Challenging Improves Cross-Domain Generalization ...
In this paper, we choose Faster R-CNN as our base detector, and improve its generalization ability for object detection in a new target domain. Domain Adaptation: Domain adaptation has been widely studied for image classification in computer vi- sion [10, 11, 33, 23, 22, 14, 52, 40, ...
object detection tasks, because in many industrial scenes (especially disaster accidents),image datais not only scarce, but also often too different from the data used for model training. Therefore, DA technology is needed to improve the cross-domaingeneralization performanceof object detection models...
* Real-Time and Robust 3D Object Detection Within Road-Side LiDARs Using Domain Adaptation* 链接: arxiv.org/abs/2204.0013* 作者: Walter Zimmer,Marcus Grabler,Alois Knoll* 摘要: 这项工作旨在解决使用基础设施Lidars对3D对象检测的域适应域的挑战。我们设计了一种模型Dase-Propillars,可以实时地检测基于...
However, this learned knowl- edge contains the domain-specific bias due to different ob- ject sizes and point densities collected by different LiDAR, leading to the poor generalization ability on the target do- main. Although Yang et al. [51] seek to overcome the bi...