41 citations · 50 across the 7 of their papers we have counts for
7 papers
Multi-view Adversarial Discriminator: Mine the Non-causal Factors for Object Detection in Unseen Domains
Mingjun Xu, Lingyun Qin, Weijie Chen +2
Domain shift degrades the performance of object detection models in practical applications. To alleviate the influence of domain shift, plenty of previous work try to decouple and…
Adversarial Style Augmentation for Domain Generalization
Yabin Zhang, Bin Deng, Ruihuang Li +2
It is well-known that the performance of well-trained deep neural networks may degrade significantly when they are applied to data with even slightly shifted distributions. Recent…
Attention Diversification for Domain Generalization
Rang Meng, Xianfeng Li, Weijie Chen +7
Convolutional neural networks (CNNs) have demonstrated gratifying results at learning discriminative features. However, when applied to unseen domains, state-of-the-art models are…
Universal Domain Adaptive Object Detector
Wenxu Shi, Lei Zhang, Weijie Chen +1
Universal domain adaptive object detection (UniDAOD)is more challenging than domain adaptive object detection (DAOD) since the label space of the source domain may not be the same…
BP-Triplet Net for Unsupervised Domain Adaptation: A Bayesian Perspective
Shanshan Wang, Lei Zhang, Pichao Wang
Triplet loss, one of the deep metric learning (DML) methods, is to learn the embeddings where examples from the same class are closer than examples from different classes. Motivate…
Semi-Supervised Domain Generalization with Evolving Intermediate Domain
Luojun Lin, Han Xie, Zhishu Sun +4
Domain Generalization (DG) aims to generalize a model trained on multiple source domains to an unseen target domain. The source domains always require precise annotations, which ca…
Multi-adversarial Faster-RCNN for Unrestricted Object Detection
Zhenwei He, Lei Zhang
Conventional object detection methods essentially suppose that the training and testing data are collected from a restricted target domain with expensive labeling cost. For allevia…