activity
20172022
most citedEnsembles of Deep LSTM Learners for Activity Recognition using Wearables

520 citations · 796 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2022★ 1 cited

Action Quality Assessment with Temporal Parsing Transformer

Yang Bai, Desen Zhou, Songyang Zhang +5

Action Quality Assessment(AQA) is important for action understanding and resolving the task poses unique challenges due to subtle visual differences. Existing state-of-the-art meth…

cs.CV2021★ 8 cited

Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action Recognition

Tailin Chen, Desen Zhou, Jian Wang +4

The task of skeleton-based action recognition remains a core challenge in human-centred scene understanding due to the multiple granularities and large variation in human motion. E…

cs.CV2021★ 26 cited

Discriminative Latent Semantic Graph for Video Captioning

Yang Bai, Junyan Wang, Yang Long +4

Video captioning aims to automatically generate natural language sentences that can describe the visual contents of a given video. Existing generative models like encoder-decoder f…

cs.CV2020★ 17 cited

Invariant Deep Compressible Covariance Pooling for Aerial Scene Categorization

Shidong Wang, Yi Ren, Gerard Parr +2

Learning discriminative and invariant feature representation is the key to visual image categorization. In this article, we propose a novel invariant deep compressible covariance p…

cs.CV2020★ 21 cited

Query Twice: Dual Mixture Attention Meta Learning for Video Summarization

Junyan Wang, Yang Bai, Yang Long +4

Video summarization aims to select representative frames to retain high-level information, which is usually solved by predicting the segment-wise importance score via a softmax fun…

cs.LG2020★ 23 cited

Fatigue Assessment using ECG and Actigraphy Sensors

Yang Bai, Yu Guan, Wan-Fai Ng

Fatigue is one of the key factors in the loss of work efficiency and health-related quality of life, and most fatigue assessment methods were based on self-reporting, which may suf…