346 citations · 576 across the 22 of their papers we have counts for
48 papers
Semi-Supervised and Unsupervised Deep Visual Learning: A Survey
Yanbei Chen, Massimiliano Mancini, Xiatian Zhu +1
State-of-the-art deep learning models are often trained with a large amount of costly labeled training data. However, requiring exhaustive manual annotations may degrade the model'…
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…
SOS! Self-supervised Learning Over Sets Of Handled Objects In Egocentric Action Recognition
Victor Escorcia, Ricardo Guerrero, Xiatian Zhu +1
Learning an egocentric action recognition model from video data is challenging due to distractors (e.g., irrelevant objects) in the background. Further integrating object informati…
Knowledge Distillation Meets Open-Set Semi-Supervised Learning
Jing Yang, Xiatian Zhu, Adrian Bulat +2
Existing knowledge distillation methods mostly focus on distillation of teacher's prediction and intermediate activation. However, the structured representation, which arguably is…
Few-Shot Website Fingerprinting Attack
Mantun Chen, Yongjun Wang, Zhiquan Qin +1
This work introduces a novel data augmentation method for few-shot website fingerprinting (WF) attack where only a handful of training samples per website are available for deep le…
Unsupervised Noisy Tracklet Person Re-identification
Minxian Li, Xiatian Zhu, Shaogang Gong
Existing person re-identification (re-id) methods mostly rely on supervised model learning from a large set of person identity labelled training data per domain. This limits their…