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Crowd Counting

21 papers with code ยท Computer Vision
Subtask of Crowds

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Improving the Learning of Multi-column Convolutional Neural Network for Crowd Counting

17 Sep 2019

By minimizing the mutual information, each column is guided to learn features with different image scales.

CROWD COUNTING

Learning Spatial Awareness to Improve Crowd Counting

16 Sep 2019

Although the Maximum Excess over SubArrays (MESA) loss has been previously proposed to address the above issues by finding the rectangular subregion whose predicted density map has the maximum difference from the ground truth, it cannot be solved by gradient descent, thus can hardly be integrated into the deep learning framework.

CROWD COUNTING

Perspective-Guided Convolution Networks for Crowd Counting

16 Sep 2019

In this paper, we propose a novel perspective-guided convolution (PGC) for convolutional neural network (CNN) based crowd counting (i. e. PGCNet), which aims to overcome the dramatic intra-scene scale variations of people due to the perspective effect.

CROWD COUNTING

Crowd Counting on Images with Scale Variation and Isolated Clusters

9 Sep 2019

Designing a general crowd counting algorithm applicable to a wide range of crowd images is challenging, mainly due to the possibly large variation in object scales and the presence of many isolated small clusters.

CROWD COUNTING

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting

28 Aug 2019

These issues are further exacerbated in highly congested scenes.

CROWD COUNTING

Robust Regression via Deep Negative Correlation Learning

24 Aug 2019

Nonlinear regression has been extensively employed in many computer vision problems (e. g., crowd counting, age estimation, affective computing).

AGE ESTIMATION CROWD COUNTING IMAGE SUPER-RESOLUTION

Crowd Counting with Deep Structured Scale Integration Network

23 Aug 2019

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.

CROWD COUNTING REPRESENTATION LEARNING

From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer

15 Aug 2019

A dense region can always be divided until sub-region counts are within the previously observed closed set.

CROWD COUNTING

Enhanced 3D convolutional networks for crowd counting

12 Aug 2019

Recently, convolutional neural networks (CNNs) are the leading defacto method for crowd counting.

CROWD COUNTING

SCAR: Spatial-/Channel-wise Attention Regression Networks for Crowd Counting

10 Aug 2019

The latter attempts to extract more discriminative features among different channels, which aids model to pay attention to the head region, the core of crowd scenes.

CROWD COUNTING