177 citations · 247 across the 11 of their papers we have counts for
11 papers
Multimodal Semi-Supervised Learning for 3D Objects
Zhimin Chen, Longlong Jing, Yang Liang +2
In recent years, semi-supervised learning has been widely explored and shows excellent data efficiency for 2D data. There is an emerging need to improve data efficiency for 3D task…
Cross-modal Center Loss
Longlong Jing, Elahe Vahdani, Jiaxing Tan +1
Cross-modal retrieval aims to learn discriminative and modal-invariant features for data from different modalities. Unlike the existing methods which usually learn from the feature…
Self-supervised Modal and View Invariant Feature Learning
Longlong Jing, Yucheng Chen, Ling Zhang +2
Most of the existing self-supervised feature learning methods for 3D data either learn 3D features from point cloud data or from multi-view images. By exploring the inherent multi-…
Recognizing American Sign Language Nonmanual Signal Grammar Errors in Continuous Videos
Elahe Vahdani, Longlong Jing, Yingli Tian +1
As part of the development of an educational tool that can help students achieve fluency in American Sign Language (ASL) through independent and interactive practice with immediate…
Self-supervised Feature Learning by Cross-modality and Cross-view Correspondences
Longlong Jing, Yucheng Chen, Ling Zhang +2
The success of supervised learning requires large-scale ground truth labels which are very expensive, time-consuming, or may need special skills to annotate. To address this issue,…
VideoSSL: Semi-Supervised Learning for Video Classification
Longlong Jing, Toufiq Parag, Zhe Wu +2
We propose a semi-supervised learning approach for video classification, VideoSSL, using convolutional neural networks (CNN). Like other computer vision tasks, existing supervised…