Web: http://arxiv.org/abs/2205.03307

May 9, 2022, 1:10 a.m. | Jiaqi Gao, Jingqi Li, Hongming Shan, Yanyun Qu, James Z. Wang, Junping Zhang

cs.CV updates on arXiv.org arxiv.org

Crowd Counting has important applications in public safety and pandemic
control. A robust and practical crowd counting system has to be capable of
continuously learning with the new-coming domain data in real-world scenarios
instead of fitting one domain only. Off-the-shelf methods have some drawbacks
to handle multiple domains. 1) The models will achieve limited performance
(even drop dramatically) among old domains after training images from new
domains due to the discrepancies of intrinsic data distributions from various
domains, which is …

arxiv benchmark count cv distillation incremental learning

More from arxiv.org / cs.CV updates on arXiv.org

Predictive Ecology Postdoctoral Fellow

@ Lawrence Berkeley National Lab | Berkeley, CA

Data Analyst, Patagonia Action Works

@ Patagonia | Remote

Data & Insights Strategy & Innovation General Manager

@ Chevron Services Company, a division of Chevron U.S.A Inc. | Houston, TX

Faculty members in Research areas such as Bayesian and Spatial Statistics; Data Privacy and Security; AI/ML; NLP; Image and Video Data Analysis

@ Ahmedabad University | Ahmedabad, India

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL