From open set to closed set: Counting objects by spatial divide-and-conquer
Visual counting, a task that predicts the number of objects from an image/video, is an open-
set problem by nature, ie, the number of population can vary in [0,+[?]) in theory. However …
set problem by nature, ie, the number of population can vary in [0,+[?]) in theory. However …
Rethinking spatial invariance of convolutional networks for object counting
Previous work generally believes that improving the spatial invariance of convolutional
networks is the key to object counting. However, after verifying several mainstream counting …
networks is the key to object counting. However, after verifying several mainstream counting …
Weakly-supervised crowd counting learns from sorting rather than locations
In crowd counting datasets, the location labels are costly, yet, they are not taken into the
evaluation metrics. Besides, existing multi-task approaches employ high-level tasks to …
evaluation metrics. Besides, existing multi-task approaches employ high-level tasks to …
Scale pyramid network for crowd counting
Crowd counting is a concerned yet challenging task in computer vision. The difficulty is
particularly pronounced by scale variations in crowd images. Most state-of-art approaches …
particularly pronounced by scale variations in crowd images. Most state-of-art approaches …
Adaptive mixture regression network with local counting map for crowd counting
The crowd counting task aims at estimating the number of people located in an image or a
frame from videos. Existing methods widely adopt density maps as the training targets to …
frame from videos. Existing methods widely adopt density maps as the training targets to …
Encoder-decoder based convolutional neural networks with multi-scale-aware modules for crowd counting
In this paper, we propose two modified neural networks based on dual path multi-scale
fusion networks (SFANet) and SegNet for accurate and efficient crowd counting. Inspired by …
fusion networks (SFANet) and SegNet for accurate and efficient crowd counting. Inspired by …
Crowd counting with deep structured scale integration network
Automatic estimation of the number of people in unconstrained crowded scenes is a
challenging task and one major difficulty stems from the huge scale variation of people. In …
challenging task and one major difficulty stems from the huge scale variation of people. In …
DSPNet: Deep scale purifier network for dense crowd counting
Crowd counting has produced considerable concern in recent years. However, crowd
counting in highly congested scenes is a challenging problem owing to scale variation. To …
counting in highly congested scenes is a challenging problem owing to scale variation. To …
[HTML][HTML] Multi-scale dilated convolution of convolutional neural network for crowd counting
Y Wang, S Hu, G Wang, C Chen, Z Pan - Multimedia Tools and …, 2020 - Springer
Growing numbers of crowd density estimation methods have been developed in scene
monitoring, crowd safety and on-site management scheduling. We proposed a method for …
monitoring, crowd safety and on-site management scheduling. We proposed a method for …
Crowd counting with partial annotations in an image
To fully leverage the data captured from different scenes with different view angles while
reducing the annotation cost, this paper studies a novel crowd counting setting, ie only using …
reducing the annotation cost, this paper studies a novel crowd counting setting, ie only using …