使用上述方法可以使用item id的embedding和side information特征信息获得item细粒度的表征V,但还缺少一个明确的监督信号,因此文中引入了一个先验信息,即学到的item表征应该更接近item id的embdding。基于这个想法,论文中设计了两个Alignment Loss用来对齐item id的embdding和特征分离表征这两部分信息,loss的定义如公式(5...
Loss function也非常直观,首先是partial feature branch部分的loss,上面提到了每一个part都会预测一个id,因此这里的id loss是cross entropy的和:yi是每个part的id预测结果,y是ground truth,CE代表cross entropy。 而对于pose guided branch来说,loss同样直观,通过最后的feature vector会预测一个id,因此这里还是id loss,...
For domain generalization (DG) and unsupervised domain adaptation (UDA), cross domain feature alignment has been widely explored to pull the feature distributions of different domains in order to learn domain-invariant representations. However, the feature alignment is in general task-ignorant and could...
提出了一个逐步特征对齐网络 Progressive Feature Alignment Network (PFAN)去解决原域有标签、目标域无标签的无监督domain adaptation分类问题: Easy-to-Hard 迁移策略 (EHTS): 利用跨模态相似度逐步选择可靠的伪标签 自适应原型对齐 Adapative Prototype Alignment (APA): 对于每个类别,将原域和目标域的prototypes对齐...
In this article, we propose a bi-temporal feature alignment and refinement network (FARNet). To improve the discriminative capability of the Siamese network, an adversarial learning-based temporal discriminatory loss function is designed to align temporal-level features and eliminate bi-temporal domain...
同意 @周翼南的看法, 这个cocoloss其实平平无奇, 真正work的是对齐? 这个之前倒是没想到. 仅仅用soft...
Multi-classifier alignment loss was constructed to improve the diagnostic accuracy of samples near the decision boundary. Wang et al. [21] proposed a deep adversarial domain adaptation network based on the Wasserstein distance to transfer fault diagnosis knowledge. In [22], a fine-grained ...
Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector,摘要域适配目标检测旨在将目标检测器适配到未知的域,新的域可能会遇到各种各样的外观变化,包括外观,视角或者背景。现存的大多数方法在图像级或者实例级上采用图像对齐的方法
之后使用reconstruction generator Gr 来保证生成的target-like image 能保留source domain image 中的结构信息。 Gr 使用cycle consistency loss进行优化:(2)Lcyc=Exs∼IS[||xs→t→s−xs||1 (3)L1=LGAN+λ1Lcyc Content and Style Feature Alignment ...
论文阅读笔记之RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment,程序员大本营,技术文章内容聚合第一站。