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A Survey on Deep Learning-based Single Image Crowd Counting: Network
  Design, Loss Function and Supervisory Signal
v1v2 (latest)

A Survey on Deep Learning-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory Signal

Neurocomputing (Neurocomputing), 2020
31 December 2020
Haoyue Bai
Jiageng Mao
Shueng-Han Gary Chan
ArXiv (abs)PDFHTML

Papers citing "A Survey on Deep Learning-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory Signal"

6 / 6 papers shown
L2HCount:Generalizing Crowd Counting from Low to High Crowd Density via Density Simulation
L2HCount:Generalizing Crowd Counting from Low to High Crowd Density via Density Simulation
Guoliang Xu
Jianqin Yin
Ren Zhang
Yonghao Dang
Feng Zhou
Bo Yu
358
0
0
17 Mar 2025
A Survey on Class-Agnostic Counting: Advancements from Reference-Based to Open-World Text-Guided Approaches
A Survey on Class-Agnostic Counting: Advancements from Reference-Based to Open-World Text-Guided Approaches
Luca Ciampi
Ali Azmoudeh
Elif Ecem Akbaba
Erdi Sarıtaş
Ziya Ata Yazıcı
H. K. Ekenel
Giuseppe Amato
Fabrizio Falchi
736
3
0
31 Jan 2025
Accelerating Deep Learning with Fixed Time Budget
Accelerating Deep Learning with Fixed Time Budget
Muhammad Asif Khan
R. Hamila
Hamid Menouar
302
1
0
03 Oct 2024
Mask Focal Loss: A unifying framework for dense crowd counting with
  canonical object detection networks
Mask Focal Loss: A unifying framework for dense crowd counting with canonical object detection networks
Xiaopin Zhong
Guan Wang
Weixiang Liu
Zongze Wu
Yuanlong Deng
453
9
0
22 Dec 2022
Revisiting Crowd Counting: State-of-the-art, Trends, and Future
  Perspectives
Revisiting Crowd Counting: State-of-the-art, Trends, and Future PerspectivesImage and Vision Computing (IVC), 2022
Muhammad Asif Khan
Hamid Menouar
R. Hamila
HAI
299
78
0
14 Sep 2022
MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation
MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation
Abhay Kumar
Nishant Jain
Suraj Tripathi
Chirag Singh
K. Krishna
239
3
0
23 Aug 2019
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