activity
20102022
most citedMulti-Granularity Canonical Appearance Pooling for Remote Sensing Scene Classification

135 citations · 164 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2022

Audio-Adaptive Activity Recognition Across Video Domains

Yunhua Zhang, Hazel Doughty, Ling Shao +1

This paper strives for activity recognition under domain shift, for example caused by change of scenery or camera viewpoint. The leading approaches reduce the shift in activity app…

cs.CV20213 cited

Anchor-free 3D Single Stage Detector with Mask-Guided Attention for Point Cloud

Jiale Li, Hang Dai, Ling Shao +1

Most of the existing single-stage and two-stage 3D object detectors are anchor-based methods, while the efficient but challenging anchor-free single-stage 3D object detection is no…

cs.CV202017 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.CV2020135 cited

Multi-Granularity Canonical Appearance Pooling for Remote Sensing Scene Classification

S. Wang, Y. Guan, L. Shao

Recognising remote sensing scene images remains challenging due to large visual-semantic discrepancies. These mainly arise due to the lack of detailed annotations that can be emplo…

cs.CV2018

3D PersonVLAD: Learning Deep Global Representations for Video-based Person Re-identification

Lin Wu, Yang Wang, Ling Shao +1

In this paper, we introduce a global video representation to video-based person re-identification (re-ID) that aggregates local 3D features across the entire video extent. Most of…

cs.CV20114 cited

An Algorithm for Repairing Low-Quality Video Enhancement Techniques Based on Trained Filter

Lijun Wang, Ling Shao

Multifarious image enhancement algorithms have been used in different applications. Still, some algorithms or modules are imperfect for practical use. When the image enhancement mo…