Wide-Area Crowd Counting: Multi-View Fusion Networks for Counting in Large Scenes

  title={Wide-Area Crowd Counting: Multi-View Fusion Networks for Counting in Large Scenes},
  author={Qi Zhang and Antoni B. Chan},
Crowd counting in single-view images has achieved outstanding performance on existing counting datasets. However, single-view counting is not applicable to large and wide scenes (e.g., public parks, long subway platforms, or event spaces) because a single camera cannot capture the whole scene in adequate detail for counting, e.g., when the scene is too large to fit into the field-of-view of the camera, too long so that the resolution is too low on faraway crowds, or when there are too many… 
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Wide-Area Crowd Counting via Ground-Plane Density Maps and Multi-View Fusion CNNs
  • Qi Zhang, Antoni B. Chan
  • Computer Science
    2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2019
A deep neural network framework for multi-view crowd counting, which fuses information from multiple camera views to predict a scene-level density map on the ground-plane of the 3D world is proposed.
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