22 citations · 62 across the 12 of their papers we have counts for
4 papers · 1 filter
Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering
Yongyi Su, Xun Xu, Kui Jia
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…
SemiCurv: Semi-Supervised Curvilinear Structure Segmentation
Xun Xu, Manh Cuong Nguyen, Yasin Yazici +3
Recent work on curvilinear structure segmentation has mostly focused on backbone network design and loss engineering. The challenge of collecting labelled data, an expensive and la…
Revisiting Pretraining for Semi-Supervised Learning in the Low-Label Regime
Xun Xu, Jingyi Liao, Lile Cai +5
Semi-supervised learning (SSL) addresses the lack of labeled data by exploiting large unlabeled data through pseudolabeling. However, in the extremely low-label regime, pseudo labe…
Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding
Xian Shi, Xun Xu, Wanyue Zhang +3
Semantic understanding of 3D point cloud relies on learning models with massively annotated data, which, in many cases, are expensive or difficult to collect. This has led to an em…