activity
20152020
most citedImproving Relation Extraction with Knowledge-attention

27 citations · 35 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20202 cited

Effective Action Recognition with Embedded Key Point Shifts

Haozhi Cao, Yuecong Xu, Jianfei Yang +3

Temporal feature extraction is an essential technique in video-based action recognition. Key points have been utilized in skeleton-based action recognition methods but they require…

cs.CV2020

PNL: Efficient Long-Range Dependencies Extraction with Pyramid Non-Local Module for Action Recognition

Yuecong Xu, Haozhi Cao, Jianfei Yang +3

Long-range spatiotemporal dependencies capturing plays an essential role in improving video features for action recognition. The non-local block inspired by the non-local means is…

cs.CV20202 cited

Exploiting Inter-Frame Regional Correlation for Efficient Action Recognition

Yuecong Xu, Jianfei Yang, Kezhi Mao +2

Temporal feature extraction is an important issue in video-based action recognition. Optical flow is a popular method to extract temporal feature, which produces excellent performa…

cs.CL201927 cited

Improving Relation Extraction with Knowledge-attention

Pengfei Li, Kezhi Mao, Xuefeng Yang +1

While attention mechanisms have been proven to be effective in many NLP tasks, majority of them are data-driven. We propose a novel knowledge-attention encoder which incorporates p…

cs.CL20154 cited

Supervised Fine Tuning for Word Embedding with Integrated Knowledge

Xuefeng Yang, Kezhi Mao

Learning vector representation for words is an important research field which may benefit many natural language processing tasks. Two limitations exist in nearly all available mode…