40 citations · 113 across the 31 of their papers we have counts for
9 papers · 1 filter
SEA++: Multi-Graph-based High-Order Sensor Alignment for Multivariate Time-Series Unsupervised Domain Adaptation
Yucheng Wang, Yuecong Xu, Jianfei Yang +4
Unsupervised Domain Adaptation (UDA) methods have been successful in reducing label dependency by minimizing the domain discrepancy between a labeled source domain and an unlabeled…
MoPA: Multi-Modal Prior Aided Domain Adaptation for 3D Semantic Segmentation
Haozhi Cao, Yuecong Xu, Jianfei Yang +3
Multi-modal unsupervised domain adaptation (MM-UDA) for 3D semantic segmentation is a practical solution to embed semantic understanding in autonomous systems without expensive poi…
Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data
Yucheng Wang, Yuecong Xu, Jianfei Yang +4
Multivariate Time-Series (MTS) data is crucial in various application fields. With its sequential and multi-source (multiple sensors) properties, MTS data inherently exhibits Spati…
Graph-Aware Contrasting for Multivariate Time-Series Classification
Yucheng Wang, Yuecong Xu, Jianfei Yang +4
Contrastive learning, as a self-supervised learning paradigm, becomes popular for Multivariate Time-Series (MTS) classification. It ensures the consistency across different views o…
Can We Evaluate Domain Adaptation Models Without Target-Domain Labels?
Jianfei Yang, Hanjie Qian, Yuecong Xu +2
Unsupervised domain adaptation (UDA) involves adapting a model trained on a label-rich source domain to an unlabeled target domain. However, in real-world scenarios, the absence of…
MM-Fi: Multi-Modal Non-Intrusive 4D Human Dataset for Versatile Wireless Sensing
Jianfei Yang, He Huang, Yunjiao Zhou +6
4D human perception plays an essential role in a myriad of applications, such as home automation and metaverse avatar simulation. However, existing solutions which mainly rely on c…
Multi-Modal Continual Test-Time Adaptation for 3D Semantic Segmentation
Haozhi Cao, Yuecong Xu, Jianfei Yang +3
Continual Test-Time Adaptation (CTTA) generalizes conventional Test-Time Adaptation (TTA) by assuming that the target domain is dynamic over time rather than stationary. In this pa…
Augmenting and Aligning Snippets for Few-Shot Video Domain Adaptation
Yuecong Xu, Jianfei Yang, Yunjiao Zhou +3
For video models to be transferred and applied seamlessly across video tasks in varied environments, Video Unsupervised Domain Adaptation (VUDA) has been introduced to improve the…
Confidence Attention and Generalization Enhanced Distillation for Continuous Video Domain Adaptation
Xiyu Wang, Yuecong Xu, Jianfei Yang +2
Continuous Video Domain Adaptation (CVDA) is a scenario where a source model is required to adapt to a series of individually available changing target domains continuously without…