18 citations · 18 across the 2 of their papers we have counts for
3 papers
cs.CV2022
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…
cs.CV2021★ 18 cited
Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach
Xian Shi, Xun Xu, Ke Chen +3
Deep learning models are the state-of-the-art methods for semantic point cloud segmentation, the success of which relies on the availability of large-scale annotated datasets. Howe…
cs.NE2018
TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks
Lile Cai, Anne-Maelle Barneche, Arthur Herbout +4
Embedded deep learning platforms have witnessed two simultaneous improvements. First, the accuracy of convolutional neural networks (CNNs) has been significantly improved through t…