activity
20182022
most citedSo2Sat LCZ42: A Benchmark Dataset for Global Local Climate Zones Classification

53 citations · 101 across the 5 of their papers we have counts for

collaborators

10 papers

cs.CV202216 cited

FuTH-Net: Fusing Temporal Relations and Holistic Features for Aerial Video Classification

Pu Jin, Lichao Mou, Yuansheng Hua +2

Unmanned aerial vehicles (UAVs) are now widely applied to data acquisition due to its low cost and fast mobility. With the increasing volume of aerial videos, the demand for automa…

cs.CV2021

Aerial Scene Understanding in The Wild: Multi-Scene Recognition via Prototype-based Memory Networks

Yuansheng Hua, Lichao Moua, Jianzhe Lin +2

Aerial scene recognition is a fundamental visual task and has attracted an increasing research interest in the last few years. Most of current researches mainly deploy efforts to c…

eess.IV2020

CG-Net: Conditional GIS-aware Network for Individual Building Segmentation in VHR SAR Images

Yao Sun, Yuansheng Hua, Lichao Mou +1

Object retrieval and reconstruction from very high resolution (VHR) synthetic aperture radar (SAR) images are of great importance for urban SAR applications, yet highly challenging…

cs.CV20202 cited

Instance segmentation of buildings using keypoints

Qingyu Li, Lichao Mou, Yuansheng Hua +4

Building segmentation is of great importance in the task of remote sensing imagery interpretation. However, the existing semantic segmentation and instance segmentation methods oft…

cs.CV202030 cited

Ambient Sound Helps: Audiovisual Crowd Counting in Extreme Conditions

Di Hu, Lichao Mou, Qingzhong Wang +4

Visual crowd counting has been recently studied as a way to enable people counting in crowd scenes from images. Albeit successful, vision-based crowd counting approaches could fail…

cs.CV2020

ERA: A Dataset and Deep Learning Benchmark for Event Recognition in Aerial Videos

Lichao Mou, Yuansheng Hua, Pu Jin +1

Along with the increasing use of unmanned aerial vehicles (UAVs), large volumes of aerial videos have been produced. It is unrealistic for humans to screen such big data and unders…