111 citations · 118 across the 5 of their papers we have counts for
5 papers
Semi-Supervised Object Detection with Uncurated Unlabeled Data for Remote Sensing Images
Nanqing Liu, Xun Xu, Yingjie Gao +1
Annotating remote sensing images (RSIs) presents a notable challenge due to its labor-intensive nature. Semi-supervised object detection (SSOD) methods tackle this issue by generat…
STFAR: Improving Object Detection Robustness at Test-Time by Self-Training with Feature Alignment Regularization
Yijin Chen, Xun Xu, Yongyi Su +1
Domain adaptation helps generalizing object detection models to target domain data with distribution shift. It is often achieved by adapting with access to the whole target domain…
Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training
Yongyi Su, Xun Xu, Tianrui Li +1
Deploying models on target domain data subject to distribution shift requires adaptation. Test-time training (TTT) emerges as a solution to this adaptation under a realistic scenar…
On Automatic Data Augmentation for 3D Point Cloud Classification
Wanyue Zhang, Xun Xu, Fayao Liu +2
Data augmentation is an important technique to reduce overfitting and improve learning performance, but existing works on data augmentation for 3D point cloud data are based on heu…
Multi-Task Zero-Shot Action Recognition with Prioritised Data Augmentation
Xun Xu, Timothy M. Hospedales, Shaogang Gong
Zero-Shot Learning (ZSL) promises to scale visual recognition by bypassing the conventional model training requirement of annotated examples for every category. This is achieved by…