36 citations · 88 across the 9 of their papers we have counts for
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cs.CV2020
Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics
Yuxuan Liang, Kun Ouyang, Yiwei Wang +4
Citywide crowd flow analytics is of great importance to smart city efforts. It aims to model the crowd flow (e.g., inflow and outflow) of each region in a city based on historical…
cs.CV2019
Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks
Junkai Sun, Junbo Zhang, Qiaofei Li +3
Being able to predict the crowd flows in each and every part of a city, especially in irregular regions, is strategically important for traffic control, risk assessment, and public…
cs.CV2019
UrbanFM: Inferring Fine-Grained Urban Flows
Yuxuan Liang, Kun Ouyang, Lin Jing +5
Urban flow monitoring systems play important roles in smart city efforts around the world. However, the ubiquitous deployment of monitoring devices, such as CCTVs, induces a long-l…