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Awesome-Crowd-Counting
Awesome Crowd Counting
https://github.com/gjy3035/Awesome-Crowd-Counting
Last synced: 5 days ago
JSON representation
-
Papers
-
Journal
- W-VLAD
- GMLCNN
- PaDNet
- MAN
- CCLL
- MobileCount
- Deem
- CLPC
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- AGK - learning-for-manatee-counting)]
- PESSNet
- MRL
- CDENet
- FLCC
- MGANet
- HMoDE - Multi-Scale-Neural-Network-for-Crowd-Counting)]
- SS-DCNet - DCNet](#S-DCNet))
- SSL-FT
- FRVCC
- FLCB
- STGN
- CmCaF
- STC-Crowd
- LMSFFNet
- DDMD
- UCCF
- DASECount
- CrowdMLP
- MTSS
- PSGCNet
- MVMS
- DEFNet
- CLRNet
- AGCCM
- GNA - Dataset)]
- LibraNet+DQN
- NDConv
- RAN
- HANet
- STNet
- SGANet
- CTASNet
- SSR-HEF
- SSCC
- SL-ViT
- DCST
- [paper
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- EPF - Flows)]
- LA-Batch
- AutoScale - liang/AutoScale)]
- DSACA - CV/DSACA)]
- NLT
- DACC
- MATT
- TBC
- FGCC
- EPA
- PFDNet
- STDNet
- AdaCrowd
- DCANet - Yan/DCANet)]
- PDANet
- ScSiNet
- PRM
- DeepCorn
- JHU-CROWD - DRCN](#CG-DRCN))
- LSC-CNN - iisc/lsc-cnn)]
- PWCU - SFCN.svg?logo=github&label=Stars)
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- BNFDD
- FADA
- MS-GAN
- DCL - CrowdCounting)]
- ZoomCount
- DensityCNN
- DENet
- CLPNet
- FMLF
- MLSTN
- SRN+PS
- ASDF
- CAT-CNN
- RRP
- SCAN
- MobileCount
- TAN
- MH-METRONET - lecce/mh-metronet/src/master/)]
- D-ConvNet - ConvNet](#D-ConvNet))[[Project](https://mmcheng.net/dncl/)]
- SL2R
- Deem
- CLPC
- MAN
- [paper
- CCLL
- GMLCNN
- HA-CCN
- PaDNet
- LDL
- ACSPNet
- DDCN
- MRA-CNN
- ACM-CNN
- SDA-MCNN
- SCAR
- BSAD
- W-VLAD
- Improved SaCNN
- DA-Net - 777/DA-Net)]
- DAL-SVR
- CNN-MRF - counting)]
- FU 2015
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- MobileCount
- D-ConvNet - ConvNet](#D-ConvNet))[[Project](https://mmcheng.net/dncl/)]
- Deem
- CLPC
- MAN
- CCLL
- GMLCNN
- PaDNet
- W-VLAD
- W-VLAD
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- BNFDD
- MS-GAN
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- MobileCount
- D-ConvNet - ConvNet](#D-ConvNet))[[Project](https://mmcheng.net/dncl/)]
- Deem
- CLPC
- MAN
- CCLL
- GMLCNN
- PaDNet
- W-VLAD
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- BNFDD
- MS-GAN
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- MobileCount
- D-ConvNet - ConvNet](#D-ConvNet))[[Project](https://mmcheng.net/dncl/)]
- Deem
- CLPC
- MAN
- CCLL
- GMLCNN
- PaDNet
- W-VLAD
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- BNFDD
- MS-GAN
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- MobileCount
- D-ConvNet - ConvNet](#D-ConvNet))[[Project](https://mmcheng.net/dncl/)]
- Deem
- CLPC
- MAN
- CCLL
- GMLCNN
- PaDNet
- W-VLAD
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- BNFDD
- MS-GAN
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- BNFDD
- MS-GAN
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- MobileCount
- D-ConvNet - ConvNet](#D-ConvNet))[[Project](https://mmcheng.net/dncl/)]
- Deem
- CLPC
- MAN
- CCLL
- GMLCNN
- PaDNet
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- BNFDD
- MS-GAN
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- MobileCount
- D-ConvNet - ConvNet](#D-ConvNet))[[Project](https://mmcheng.net/dncl/)]
- Deem
- CLPC
- MAN
- CCLL
- GMLCNN
- PaDNet
- W-VLAD
- MobileCount
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- BNFDD
- MS-GAN
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- D-ConvNet - ConvNet](#D-ConvNet))[[Project](https://mmcheng.net/dncl/)]
- Deem
- CLPC
- MAN
- CCLL
- GMLCNN
- PaDNet
- W-VLAD
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- MS-GAN
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- MobileCount
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- MS-GAN
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- MobileCount
- Deem
- CLPC
- MAN
- CCLL
- GMLCNN
- PaDNet
- W-VLAD
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- [paper - with-Focus-for-Free)] (extension of [CFF](#CFF))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- PML_Loss - AP/PML_Loss)]
- EoCo
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- MS-GAN
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- MobileCount
- Deem
- CLPC
- MAN
- CCLL
- GMLCNN
- PaDNet
- W-VLAD
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- DPDNet - lab/Locating_Counting_with_a_Depth_Prior)]
- AutoScale - liang/AutoScale)]
- DCANet - Yan/DCANet)]
- CRNet - Counting-via-Cross-stage-Refinement-Networks)] 
- MS-GAN
- DCL - CrowdCounting)]
- DensityCNN
- CLPNet
- FMLF
- MobileCount
- Deem
- CLPC
- MAN
- CCLL
- GMLCNN
- PaDNet
- W-VLAD
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- Multimodal-SDA
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- FIDTM - liang/FIDTM)] [[project](https://dk-liang.github.io/FIDTM/)]
- TransCrowd - liang/TransCrowd)]
- AutoScale - liang/AutoScale)]
- D2C - Stage_Counting)]
- PSODC - supervised-crowd-detection)]
- NWPU - Crowd-Sample-Code/)]
- KDMG - wan/KDMG_Counting)]
- MobileCount
- PCC-Net - Net)]
- NetVLAD - Multiscale-Deep-NetVLAD)]
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- ECCNAS
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- Improved SaCNN
- DA-Net - 777/DA-Net)]
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- [paper
- HKINet
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- MobileCount
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- HPS
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
- [paper
- AGK - learning-for-manatee-counting)]
- SS-DCNet - DCNet](#S-DCNet))
- FLCB
- AutoScale - liang/AutoScale)]
- MobileCount
-
Conference
- MVSAN
- A-CCNN
- [paper
- MS-GAN
- GAN-MTR
- SRF-Net
- CWAN
- AGRD
- BBA-NET
- SMANet
- mPrompt
- SGA
- SRN
- STEERER
- PET
- [paper
- CU
- DAOT
- DDC
- CrowdCLIP
- SAFECount
- DMCNet
- CACC
- CHS-Net
- Self-ONN
- TSFADet
- CSCA
- CUT
- MSDTrans
- LoViTCrowd
- SPDCN
- CF-MVCC
- DC
- ChfL
- DR.VIC
- LibraNet
- BLA
- CrowdFormer
- WSCNN
- STAN
- LARL
- ESA-Net
- TAFNet
- HDNet
- SSDA
- FusionCount
- GNet
- PFSNet
- URC
- MFDC
- SDNet
- SUA
- CC-AV
- BinLoss
- ASNet
- S3
- BM-Count
- GLoss
- CVCS
- STANet
- UOT
- TopoCount
- CFANet
- BSCC
- SCALNet
- FCVF
- IDK
- CRANet
- MNA
- DPN
- RDBT
- VisDrone-CC2020
- AMSNet
- GP
- IRAST
- PSSW
- CCLS
- Bi-pathNet
- ADSCNet
- RPNet
- ASNet
- SRF-Net
- PRM
- HSRNet
- DeepCount
- SOFA-Net
- CWAN
- AGRD
- BBA-NET
- SMANet
- MSPNET
- ASPDNet
- FSC
- C-CNN
- HyGnn
- DUBNet
- SDANet
- 3DCC - 3d-counting/)]
- FSSA
- CC-Mod
- CTN
- ikNN
- CG-DRCN
- ADMG
- DSSINet - ICCV-DSSINet)] 
- RANet
- ANF
- SPANet
- MBTTBF
- CFF - with-Focus-for-Free)] 
- L2SM
- S-DCNet - hust-2018-2011/S-DCNet)]
- BL - Crowd-Counting)] 
- PGCNet - Yan/PGCNet)]
- SACANet
- McML
- DADNet
- MRNet
- MRCNet
- E3D
- OSSS
- RAZ-Net
- RDNet - lab/RGBD-Counting)] 
- RRSP - wan/ResidualRegression-pytorch)] 
- MVMS
- AT-CFCN
- TEDnet
- PACNN
- PSDDN
- ADCrowdNet
- DG-GAN
- GSP
- IA-DNN
- MTCNet
- CODA
- LSTN
- DRD
- MVSAN
- ASD
- SAAN
- SPN
- GWTA-CCNN
- GPC
- AM-CNN
- CRDNet
- SANet
- ic-CNN
- CL
- LCFCN
- CSR - pytorch)]
- L2R
- ACSCP - ACSCP)]
- DecideNet
- AMDCN
- D-ConvNet - NCL)]
- [paper
- SCNet
- AFP
- DRSAN
- TDF-CNN
- A-CCNN
- [paper
- MS-GAN
- DR-ResNet
- GAN-MTR
- SaCNN - CrowdCounting-Tencent_Youtu)]
- CP-CNN
- ConvLSTM
- ResnetCrowd
- ACNN
- FCNCC
- MCNN - vora/crowd_counting_tensorflow)  [PyTorch](https://github.com/svishwa/crowdcount-mcnn)]
- Hydra-CNN
- CNN-Boosting
- Crossing-line
- GP
- CrowdNet - crowd-counting_crowdnet)]
- Shang 2016
- DE-VOC
- RPF
- CS-SLR
- Faster-OHEM-KCF
- [paper
- Bayesian
- Zhang 2015
- Wang 2015
- Arteta 2014
- Idrees 2013
- Ma 2013
- Chen 2013
- SSR
- Chen 2012
- Rodriguez 2011
- Lempitsky 2010
- Chan 2008
- GAN-MTR
- FCVF
- IDK
- CRANet
- SRF-Net
- CWAN
- AGRD
- BBA-NET
- SMANet
- MVSAN
- A-CCNN
- [paper
- MS-GAN
- GAN-MTR
- SaCNN - CrowdCounting-Tencent_Youtu)]
- Shang 2016
- RPF
- CS-SLR
- FCVF
- IDK
- CRANet
- SRF-Net
- CWAN
- AGRD
- BBA-NET
- SMANet
- SaCNN - CrowdCounting-Tencent_Youtu)]
- Shang 2016
- RPF
- CS-SLR
- Wang 2015
- FCVF
- IDK
- CRANet
- SRF-Net
- CWAN
- AGRD
- BBA-NET
- SMANet
- MVSAN
- A-CCNN
- [paper
- MS-GAN
- GAN-MTR
- SaCNN - CrowdCounting-Tencent_Youtu)]
- Shang 2016
- RPF
- CS-SLR
- FCVF
- IDK
- CRANet
- SRF-Net
- CWAN
- AGRD
- BBA-NET
- SMANet
- RPF
- MVSAN
- A-CCNN
- [paper
- MS-GAN
- GAN-MTR
- SaCNN - CrowdCounting-Tencent_Youtu)]
- Shang 2016
- CS-SLR
- Gramformer
- FCVF
- IDK
- CRANet
- SRF-Net
- CWAN
- AGRD
- BBA-NET
- SMANet
- MVSAN
- A-CCNN
- [paper
- MS-GAN
- GAN-MTR
- SaCNN - CrowdCounting-Tencent_Youtu)]
- Shang 2016
- RPF
- CS-SLR
- FCVF
- IDK
- CRANet
- SRF-Net
- CWAN
- AGRD
- BBA-NET
- SMANet
- MVSAN
- A-CCNN
- [paper
- MS-GAN
- SaCNN - CrowdCounting-Tencent_Youtu)]
- Shang 2016
- RPF
- CS-SLR
- FCVF
- IDK
- CRANet
- MVSAN
- A-CCNN
- [paper
- MS-GAN
- GAN-MTR
- SaCNN - CrowdCounting-Tencent_Youtu)]
- Shang 2016
- RPF
- CS-SLR
- FCVF
- IDK
- CRANet
- CWAN
- AGRD
- BBA-NET
- SMANet
- A-CCNN
- [paper
- MS-GAN
- GAN-MTR
- SaCNN - CrowdCounting-Tencent_Youtu)]
- Shang 2016
- RPF
- CS-SLR
- A-CCNN
- [paper
- MS-GAN
- GAN-MTR
- SaCNN - CrowdCounting-Tencent_Youtu)]
- Shang 2016
- CS-SLR
- RPF
- [paper
- FCVF
- IDK
- CRANet
- Crowd-Hat - Hat)]
- CTFNet
- FCVF
- IDK
- CRANet
- CWAN
- AGRD
- BBA-NET
- SMANet
- MS-GAN
- GAN-MTR
- SaCNN - CrowdCounting-Tencent_Youtu)]
- FCVF
- IDK
- CRANet
- CWAN
- AGRD
- BBA-NET
- SMANet
- A-CCNN
- [paper
- Shang 2016
- RPF
- CS-SLR
- BM - Modality-Crowd-Counting)]
- CountFormer
- OALNet
- FCVF
- IDK
- CRANet
- CWAN
- AGRD
- BBA-NET
- SMANet
- A-CCNN
- [paper
- MS-GAN
- GAN-MTR
- SaCNN - CrowdCounting-Tencent_Youtu)]
- Shang 2016
- RPF
- CS-SLR
- WSCC_TAF
- DE-VOC
- ME - Monday/Multi-modal-Crowd-Counting-via-Modal-Emulation)]
- CrowdDiff
- PseCo
- EDC - VTS/TutorNet_Crowd_Counting)]
- SAM - free-object-counter)]
- AWCC-Net - Net)]
- ZSC - stonybrook/zero-shot-counting)]
- IOCFormer - Object-Counting)]
- OT-M - M)]
- DGCC - general-Crowd-Counting-in-Unseen-Scenarios)]
- MSSRM - CV/MSSRM)]
- CSS-CCNN - iisc/css-ccnn)]
- PAP - liu/PAP-Pytorch)]
- CLTR - liang/CLTR)][[project](https://dk-liang.github.io/CLTR/)]
- DACount - supervised-Crowd-Counting-via-Density-Agency)]
- GauNet - Counting)]
- CDCC - Domain-Crowd-Counting)]
- MAN - Crowd-Counting-via-Multifaceted-Attention)]
- BMNet - Matching-Network)]
- IS-Count - group/IS-Count)]
- MPS - AiimLab/crowd_counting)]
- P2PNet - P2PNet)]
- UEPNet - UEPNet)]
- DKPNet - Yan/DKPNet)]
- APAM - Crowd-analysis)]
- RGBT-CC - judge/RGBTCrowdCounting)][[Project](http://lingboliu.com/RGBT_Crowd_Counting.html#)]
- EDIREC-Net - Net)]
- SASNet - SASNet)]
- CFOCNet - agnostic-Few-shot-Object-Counting)]
- DSNet - Scale-Network-for-Crowd-Counting)]
- DM-Count - stonybrook/DM-Count)]
- SKT - SYSU/SKT)]
- EPF - Flows)]
- AMRNet - Crowd-Counting)]
- EDC - VTS/TutorNet_Crowd_Counting)]
- M-SFANet - Thanasutives/Variations-of-SFANet-for-Crowd-Counting)]
- Stacked-Pool - stackpool)]
- CAN - Aware-Crowd-Counting)]
- CCWld, SFCN - CL/)] [[arxiv](https://arxiv.org/abs/1903.03303)] 
- CAC - agnostic-counting)]
- Switching CNN - iisc/crowd-counting-scnn)]
- CMTL - cascaded-mtl)]
- MSCNN - Bao/mscnn)]
- [paper
- [paper
- MPCount
- SPN
- S-DCNet - hust-2018-2011/S-DCNet)]
- DADNet
- APGCC
- C2MoT - dq/C2MOT)]
- McML
- MRNet
- ADMG
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arXiv papers
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- [paper
- [paper
- [paper - M/CLIP-EBC)] 
- [paper
- [paper
- [paper
- [paper
- [paper - Net-Keras)]
- [paper - regulation)]
- [paper
- [paper
- [paper
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Misc
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Call for Papers
- Electronics
- Transportation Research Part C
- IET Image Processing - library.theiet.org/files/IET_IPR_CFP_CUA.pdf)]
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Challenge
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Technical blog
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GT generation
- [Matlab Code - pytorch/blob/master/make_dataset.ipynb)] [[Fast Python Code](https://github.com/vlad3996/computing-density-maps)] [[Pytorch CUDA Code](https://github.com/gjy3035/NWPU-Crowd-Sample-Code/blob/master/misc/dot_ops.py)]
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Code
- [C^3 Framework - source PyTorch code for crowd counting, which is released. 
- [CCLabeler
- [YOLO-CROWD - CROWD.svg?logo=github&label=Stars) a lightweight crowd counting and face detection model that is based on [[YOLO-FaceV2](https://github.com/Krasjet-Yu/YOLO-FaceV2)] 
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Related Tasks
- Crowd Localization - Public-Safety-in-Vision), Dense/Small/Tiny Object Detection
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Programming Languages
Categories
Sub Categories