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Article
PDDNet: lightweight congested crowd counting via pyramid depth-wise dilated convolution
The accuracy of crowd counting is susceptible to scale variations of crowd head in the congested scene. Some counting networks, such as crowd density pre-classification networks or multi-column counting networ...
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Article
SC2Net: Scale-aware Crowd Counting Network with Pyramid Dilated Convolution
Accurate crowd counting is still challenging due to the variations of crowd heads. Most of crowd counting methods adopt multi-branch networks to extract multi-scale information. However, these networks are too...
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Article
COMAL: compositional multi-scale feature enhanced learning for crowd counting
Accurately modeling the crowd’s head scale variations is an effective way to improve the counting accuracy of the crowd counting methods. Most counting networks apply a multi-branch network structure to obtain...
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Chapter and Conference Paper
MCTS-Based Robotic Exploration for Scene Graph Generation
Many researchers have used scene graphs to improve performance in some tasks in recent years, such as complete image matching, image generation, and visual questions answers. However, the current scene graph g...
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Chapter and Conference Paper
MSCANet: Adaptive Multi-scale Context Aggregation Network for Congested Crowd Counting
Crowd counting has achieved significant progress with deep convolutional neural networks. However, most of the existing methods don’t fully utilize spatial context information, and it is difficult for them to ...
