Browse > Computer Vision > Crowds > Crowd Counting

Crowd Counting

21 papers with code · Computer Vision
Subtask of Crowds

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Latest papers with code

Bayesian Loss for Crowd Count Estimation with Point Supervision

10 Aug 2019ZhihengCV/Bayesian-Crowd-Counting

In crowd counting datasets, each person is annotated by a point, which is usually the center of the head.

CROWD COUNTING

22
10 Aug 2019

Deep Density-aware Count Regressor

9 Aug 2019GeorgeChenZJ/deepcount

We seek to improve crowd counting as we perceive limits of currently prevalent density map estimation approach on both prediction accuracy and time efficiency.

CROWD COUNTING

8
09 Aug 2019

Locality-constrained Spatial Transformer Network for Video Crowd Counting

18 Jul 2019sweetyy83/Lstn_fdst_dataset

Then to relate the density maps between neighbouring frames, a Locality-constrained Spatial Transformer (LST) module is introduced to estimate the density map of next frame with that of current frame.

CROWD COUNTING

4
18 Jul 2019

C^3 Framework: An Open-source PyTorch Code for Crowd Counting

5 Jul 2019gjy3035/C-3-Framework

This technical report attempts to provide efficient and solid kits addressed on the field of crowd counting, which is denoted as Crowd Counting Code Framework (C$^3$F).

CROWD COUNTING

235
05 Jul 2019

Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection

18 Jun 2019val-iisc/lsc-cnn

We introduce a detection framework for dense crowd counting and eliminate the need for the prevalent density regression paradigm.

CROWD COUNTING

70
18 Jun 2019

PCC Net: Perspective Crowd Counting via Spatial Convolutional Network

24 May 2019gjy3035/PCC-Net

Crowd counting from a single image is a challenging task due to high appearance similarity, perspective changes and severe congestion.

CROWD COUNTING

33
24 May 2019

CODA: Counting Objects via Scale-aware Adversarial Density Adaption

25 Mar 2019Willy0919/CODA

Extensive experiments demonstrate that our network produces much better results on unseen datasets compared with existing counting adaption models.

CROWD COUNTING

14
25 Mar 2019

Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank

17 Feb 2019xialeiliu/RankIQA

Our results show that networks trained to regress to the ground truth targets for labeled data and to simultaneously learn to rank unlabeled data obtain significantly better, state-of-the-art results for both IQA and crowd counting.

ACTIVE LEARNING CROWD COUNTING IMAGE QUALITY ASSESSMENT LEARNING-TO-RANK

193
17 Feb 2019

Dual Path Multi-Scale Fusion Networks with Attention for Crowd Counting

4 Feb 2019pxq0312/SFANet-crowd-counting

The task of crowd counting in varying density scenes is an extremely difficult challenge due to large scale variations.

CROWD COUNTING

5
04 Feb 2019

Stacked Pooling: Improving Crowd Counting by Boosting Scale Invariance

22 Aug 2018siyuhuang/crowdcount-stackpool

In this work, we explore the cross-scale similarity in crowd counting scenario, in which the regions of different scales often exhibit high visual similarity.

CROWD COUNTING DENSITY ESTIMATION

73
22 Aug 2018