activity
20182021
most citedPointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation

74 citations · 105 across the 2 of their papers we have counts for

collaborators

9 papers

cs.CV202131 cited

Sign Language Recognition via Skeleton-Aware Multi-Model Ensemble

Songyao Jiang, Bin Sun, Lichen Wang +3

Sign language is commonly used by deaf or mute people to communicate but requires extensive effort to master. It is usually performed with the fast yet delicate movement of hand ge…

cs.CV2021

Skeleton Aware Multi-modal Sign Language Recognition

Songyao Jiang, Bin Sun, Lichen Wang +3

Sign language is commonly used by deaf or speech impaired people to communicate but requires significant effort to master. Sign Language Recognition (SLR) aims to bridge the gap be…

cs.CV2020

Collaborative Attention Mechanism for Multi-View Action Recognition

Yue Bai, Zhiqiang Tao, Lichen Wang +3

Multi-view action recognition (MVAR) leverages complementary temporal information from different views to improve the learning performance. Obtaining informative view-specific repr…

cs.CV2020

Contradictory Structure Learning for Semi-supervised Domain Adaptation

Can Qin, Lichen Wang, Qianqian Ma +3

Current adversarial adaptation methods attempt to align the cross-domain features, whereas two challenges remain unsolved: 1) the conditional distribution mismatch and 2) the bias…

cs.CV201974 cited

PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation

Can Qin, Haoxuan You, Lichen Wang +2

Domain Adaptation (DA) approaches achieved significant improvements in a wide range of machine learning and computer vision tasks (i.e., classification, detection, and segmentation…

cs.LG2019

Correlative Channel-Aware Fusion for Multi-View Time Series Classification

Yue Bai, Lichen Wang, Zhiqiang Tao +2

Multi-view time series classification (MVTSC) aims to improve the performance by fusing the distinctive temporal information from multiple views. Existing methods mainly focus on f…