Zhang, Q.[Qi],
Chan, A.B.[Antoni B.],
Wide-Area Crowd Counting: Multi-view Fusion Networks for Counting in
Large Scenes,
IJCV(130), No. 8, August 2022, pp. 1938-1960.
Springer DOI
2207
BibRef
Earlier:
Wide-Area Crowd Counting via Ground-Plane Density Maps and Multi-View
Fusion CNNs,
CVPR19(8289-8298).
IEEE DOI
2002
BibRef
Zhang, Q.[Qi],
Chan, A.B.[Antoni B.],
3D Crowd Counting via Geometric Attention-Guided Multi-view Fusion,
IJCV(130), No. 12, December 2022, pp. 3123-3139.
Springer DOI
2211
BibRef
Zhang, Q.[Qi],
Lin, W.[Wei],
Chan, A.B.[Antoni B.],
Cross-View Cross-Scene Multi-View Crowd Counting,
CVPR21(557-567)
IEEE DOI
2111
Training, Geometry, Adaptation models, Fuses, Layout, Cameras, Data models
BibRef
Wan, J.[Jia],
Liu, Z.Q.[Zi-Quan],
Chan, A.B.[Antoni B.],
A Generalized Loss Function for Crowd Counting and Localization,
CVPR21(1974-1983)
IEEE DOI
2111
Location awareness, Annotations,
Cost function, Bayes methods, Pattern recognition
BibRef
Yan, Z.Y.[Zhao-Yi],
Li, P.Y.[Peng-Yu],
Wang, B.[Biao],
Ren, D.W.[Dong-Wei],
Zuo, W.M.[Wang-Meng],
Towards Learning Multi-Domain Crowd Counting,
CirSysVideo(33), No. 11, November 2023, pp. 6544-6557.
IEEE DOI
2311
BibRef
Ding, G.C.[Guan-Chen],
Yang, D.[Daiqin],
Wang, T.[Tao],
Wang, S.[Sihan],
Zhang, Y.F.[Yun-Fei],
Crowd Counting via Unsupervised Cross-Domain Feature Adaptation,
MultMed(25), 2023, pp. 4665-4678.
IEEE DOI
2311
BibRef
Liu, Z.Y.[Zheng-Yi],
Tan, Y.C.[Ya-Cheng],
Wu, W.[Wei],
Tang, B.[Bin],
Dilated high-resolution network driven RGB-T multi-modal crowd
counting,
SP:IC(112), 2023, pp. 116915.
Elsevier DOI
2302
Crowd counting, RGB-T image, Multi-modal, High-resolution, Multilayer perceptron
BibRef
Zhang, S.H.[Shi-Hui],
Wang, W.[Wei],
Zhao, W.B.[Wei-Bo],
Wang, L.[Lei],
Li, Q.P.[Qun-Peng],
A cross-modal crowd counting method combining CNN and cross-modal
transformer,
IVC(129), 2023, pp. 104592.
Elsevier DOI
2301
Cross-modal crowd counting, CNN, Transformer,
Cross layer connection structure, Cross-modal attention module
BibRef
Liu, Y.B.[Yan-Bo],
Cao, G.[Guo],
Shi, B.[Boshan],
Hu, Y.X.[Ying-Xiang],
CCANet: A Collaborative Cross-Modal Attention Network for RGB-D Crowd
Counting,
MultMed(26), 2024, pp. 154-165.
IEEE DOI
2401
BibRef
Zhang, Q.[Qi],
Chan, A.B.[Antoni B.],
Calibration-Free Multi-view Crowd Counting,
ECCV22(IX:227-244).
Springer DOI
2211
BibRef
Zhang, Y.J.[You-Jia],
Choi, S.[Soyun],
Hong, S.[Sungeun],
Spatio-channel Attention Blocks for Cross-modal Crowd Counting,
ACCV22(II:22-40).
Springer DOI
2307
BibRef
Liu, L.B.[Ling-Bo],
Chen, J.Q.[Jia-Qi],
Wu, H.F.[He-Feng],
Li, G.B.[Guan-Bin],
Li, C.L.[Cheng-Long],
Lin, L.[Liang],
Cross-Modal Collaborative Representation Learning and a Large-Scale
RGBT Benchmark for Crowd Counting,
CVPR21(4821-4831)
IEEE DOI
2111
Codes, Collaboration, Benchmark testing,
Optical imaging, Pattern recognition, Task analysis
BibRef
Chen, B.H.[Bing-Hui],
Yan, Z.Y.[Zhao-Yi],
Li, K.[Ke],
Li, P.Y.[Peng-Yu],
Wang, B.[Biao],
Zuo, W.M.[Wang-Meng],
Zhang, L.[Lei],
Variational Attention: Propagating Domain-Specific Knowledge for
Multi-Domain Learning in Crowd Counting,
ICCV21(16045-16055)
IEEE DOI
2203
Training, Knowledge engineering, Benchmark testing, Data models,
Labeling, Scene analysis and understanding,
Vision applications and systems
BibRef
Liu, X.Y.[Xin-Yan],
Li, G.R.[Guo-Rong],
Han, Z.J.[Zhen-Jun],
Zhang, W.G.[Wei-Gang],
Yang, Y.F.[Yi-Fan],
Huang, Q.M.[Qing-Ming],
Sebe, N.[Nicu],
Exploiting sample correlation for crowd counting with multi-expert
network,
ICCV21(3195-3204)
IEEE DOI
2203
Training, Measurement, Deconvolution, Correlation,
Design methodology, Training data,
Efficient training and inference methods
BibRef
Kaminski, L.,
Gardzinski, P.,
Kowalak, K.,
Mackowiak, S.,
Unsupervised abnormal crowd activity detection in surveillance
systems,
WSSIP16(1-4)
IEEE DOI
1608
BibRef
Earlier: A2, A3, A1, A4:
Crowd density estimation based on voxel model in multi-view
surveillance systems,
WSSIP15(216-219)
IEEE DOI
1603
image classification
BibRef
Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Crosswalk Detection, Zebra Crossings .