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Counting People by Estimating People Flows

Counting People by Estimating People Flows

1 December 2020
Weizhe Liu
Mathieu Salzmann
Pascal Fua
    3DH
ArXivPDFHTML

Papers citing "Counting People by Estimating People Flows"

10 / 10 papers shown
Title
Counting Like Human: Anthropoid Crowd Counting on Modeling the
  Similarity of Objects
Counting Like Human: Anthropoid Crowd Counting on Modeling the Similarity of Objects
Qi. Wang
Juncheng Wang
Junyuan Gao
Yuan. Yuan
Xuelong Li
20
2
0
02 Dec 2022
Multi-view Tracking Using Weakly Supervised Human Motion Prediction
Multi-view Tracking Using Weakly Supervised Human Motion Prediction
Martin Engilberge
Weizhe Liu
Pascal Fua
VOT
HAI
25
7
0
19 Oct 2022
A Spatio-Temporal Attentive Network for Video-Based Crowd Counting
A Spatio-Temporal Attentive Network for Video-Based Crowd Counting
M. Avvenuti
Marco Bongiovanni
Luca Ciampi
Fabrizio Falchi
Claudio Gennaro
Nicola Messina
23
9
0
24 Aug 2022
Crowd Localization from Gaussian Mixture Scoped Knowledge and Scoped
  Teacher
Crowd Localization from Gaussian Mixture Scoped Knowledge and Scoped Teacher
Juncheng Wang
Junyuan Gao
Yuan. Yuan
Qi. Wang
25
16
0
12 Jun 2022
SSR-HEF: Crowd Counting with Multi-Scale Semantic Refining and Hard
  Example Focusing
SSR-HEF: Crowd Counting with Multi-Scale Semantic Refining and Hard Example Focusing
Jiwei Chen
Kewei Wang
Wen Su
Zengfu Wang
19
10
0
15 Apr 2022
Video Crowd Localization with Multi-focus Gaussian Neighborhood
  Attention and a Large-Scale Benchmark
Video Crowd Localization with Multi-focus Gaussian Neighborhood Attention and a Large-Scale Benchmark
Haopeng Li
Lingbo Liu
Kunlin Yang
Shinan Liu
Junyuan Gao
Bin Zhao
Rui Zhang
Jun Hou
39
14
0
19 Jul 2021
Leveraging Self-Supervision for Cross-Domain Crowd Counting
Leveraging Self-Supervision for Cross-Domain Crowd Counting
Weizhe Liu
N. Durasov
Pascal Fua
13
40
0
30 Mar 2021
A Survey on Deep Learning-based Single Image Crowd Counting: Network
  Design, Loss Function and Supervisory Signal
A Survey on Deep Learning-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory Signal
Haoyue Bai
Jiageng Mao
Shueng-Han Gary Chan
31
22
0
31 Dec 2020
Convolutional LSTM Network: A Machine Learning Approach for
  Precipitation Nowcasting
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Xingjian Shi
Zhourong Chen
Hao Wang
Dit-Yan Yeung
W. Wong
W. Woo
227
7,903
0
13 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
261
9,136
0
06 Jun 2015
1