38 citations · 96 across the 21 of their papers we have counts for
9 papers · 1 filter
Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans
Tai-Hsien Wu, Chunfeng Lian, Sanghee Lee +11
Accurately segmenting teeth and identifying the corresponding anatomical landmarks on dental mesh models are essential in computer-aided orthodontic treatment. Manually performing…
Sequential Joint Shape and Pose Estimation of Vehicles with Application to Automatic Amodal Segmentation Labeling
Josephine Monica, Wei-Lun Chao, Mark Campbell
Shape and pose estimation is a critical perception problem for a self-driving car to fully understand its surrounding environment. One fundamental challenge in solving this problem…
Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering
Jihyung Kil, Cheng Zhang, Dong Xuan +1
Visual question answering (VQA) is challenging not only because the model has to handle multi-modal information, but also because it is just so hard to collect sufficient training…
Few-Shot Learning with a Strong Teacher
Han-Jia Ye, Lu Ming, De-Chuan Zhan +1
Few-shot learning (FSL) aims to generate a classifier using limited labeled examples. Many existing works take the meta-learning approach, constructing a few-shot learner that can…
How to Train Your MAML to Excel in Few-Shot Classification
Han-Jia Ye, Wei-Lun Chao
Model-agnostic meta-learning (MAML) is arguably one of the most popular meta-learning algorithms nowadays. Nevertheless, its performance on few-shot classification is far behind ma…
Revisiting Document Representations for Large-Scale Zero-Shot Learning
Jihyung Kil, Wei-Lun Chao
Zero-shot learning aims to recognize unseen objects using their semantic representations. Most existing works use visual attributes labeled by humans, not suitable for large-scale…