开源软件名称(OpenSource Name):taohan10200/Awesome-Crowd-Localization
开源软件地址(OpenSource Url):https://github.com/taohan10200/Awesome-Crowd-Localization
开源编程语言(OpenSource Language):
开源软件介绍(OpenSource Introduction):Awesome-Crowd-Localization
Awesome Crowd Localization
Contents
Misc
Relaetd Tasks
Challenge
- NWPU-Crowd Localization: Link
- The 1st Tiny Object Detection Challenge: Link
Metrics
- mAP, mAR in RAZNet (namely key point evaluation in COCO: fixed sigma)
- F1-m, Precision, Recall in NWPU-Crowd (scale-aware sigma)
- MLE in LSC-CNN (distance measure)
Datasets
- NWPU-Crowd (dot, box)
- JHU-CROWD (dot, size)
- FDST (dot, box)
- Head Tracking 21 (dot, box, id) [Download]
Papers
Arxiv
- [DCST] Congested Crowd Instance Localization with Dilated Convolutional Swin Transformer [paper]
- [GNA] Video Crowd Localization with Multi-focus Gaussian Neighbor Attention and a Large-Scale Benchmark [paper]
- [SCALNet] Dense Point Prediction: A Simple Baseline for Crowd Counting and Localization [paper] [code]
- [FIDTM] Focal Inverse Distance Transform Maps for Crowd Localization and Counting in Dense Crowd [paper] [code]
- [RDTM] Reciprocal Distance Transform Maps for Crowd Counting and People Localization in Dense Crowd [paper] [code]
- Counting and Locating High-Density Objects Using Convolutional Neural Network [paper]
- [IIM] Learning Independent Instance Maps for Crowd Localization [paper] [code]
- [AutoScale] Autoscale: learning to scale for crowd counting [paper] [code]
- A Strong Baseline for Crowd Counting and Unsupervised People Localization [paper]
- Drone-based Joint Density Map Estimation, Localization and Tracking with Space-Time Multi-Scale Attention Network [paper][code]
2021
- [SA-InterNet] A-InterNet: Scale-Aware Interaction Network for Joint Crowd Counting and Localization (PRVC) [paper]
- A smartly simple way for joint crowd counting and localization (Neurocomputing) [aper]
- A Generalized Loss Function for Crowd Counting and Localization (CVPR) [paper]
- [ P2PNet] Rethinking Counting and Localization in Crowds: A Purely Point-Based Framework (ICCV) [paper]
- [D2CNet] Decoupled Two-Stage Crowd Counting and Beyond (TIP) [paper] [code]
- [Crowd-SDNet] A Self-Training Approach for Point-Supervised Object Detection and Counting in Crowds (TIP) [paper] [code]
- [TopoCount] Localization in the Crowd with Topological Constraints (AAAI2021) [paper][code]
2020
- [DD-CNN] Going Beyond the Regression Paradigm with Accurate Dot Prediction for Dense Crowds (WACV) [paper]
- [NWPU] NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization (T-PAMI) [paper][code]
- [LSC-CNN] Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection (T-PAMI) [paper][code]
- Scale Match for Tiny Person Detection (WACV) [paper][code]
2019
- Density Map Regression Guided Detection Network for RGB-D Crowd Counting and Localization (CVPR) [paper]
- Point in, Box out: Beyond Counting Persons in Crowds (CVPR) [paper]
- [RAZ_Loc] Recurrent attentive zooming for joint crowd counting and precise localization (CVPR) [paper] [Reproduction_code]
- [RDNet] Density Map Regression Guided Detection Network for RGB-D Crowd Counting and Localization (CVPR) [paper][code]
2018
- [CL] Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds (ECCV) [paper]
- [LCFCN] Where are the Blobs: Counting by Localization with Point Supervision (ECCV) [paper] [code]
- SOD-MTGAN: Small Object Detection via Multi-Task Generative Adversarial Network (ECCV) [paper]
2017
- Focal Loss for Dense Object Detection (ICCV) [paper]
- [TinyFaces] Finding tiny faces (CVPR) [paper]
- Perceptual Generative Adversarial Networks for Small Object Detection (CVPR) [paper]
2015
- Small Instance Detection by Integer Programming on Object Density Maps, (CVPR) [paper ]
- End-to-end people detection in crowded scenes (CVPR) [paper] [code]
- [Faster-RCNN] Towards real-time object detection with region proposal networks (CVPR) [paper] [code]
Leaderboard
NWPU
More detailed results are in this link.
Year--Conference/Journal |
Methods |
Backbone |
F1-measure |
Precise |
Recall |
A0~A5 |
Avg. |
2015--NIPS |
Faster RCNN |
ResNet-101 |
6.7 |
95.8 |
3.5 |
0/0.002/0.4/7.9/37.2/63.5 |
18.2 |
2017--CVPR |
TinyFaces |
ResNet-101 |
56.7 |
52.9 |
61.1 |
4.2/22.6/59.1/90.0/93.1/89.6 |
59.8 |
2019--arXiv |
VGG+GPR |
VGG-16 |
52.5 |
55.8 |
49.6 |
3.1/27.2/49.1/68.7/49.8/26.3 |
37.4 |
2019--CVPR |
RAZ_Loc |
VGG-16 |
59.8 |
66.6 |
54.3 |
3.1/27.2/49.1/68.7/49.8/26.3 |
42.4 |
2021--TIP |
Crowd-SDNet |
ResNet-50 |
63.7 |
65.1 |
62.4 |
7.3/43.7/62.4/75.7/71.2/70.2 |
55.1 |
2021--AAAI |
TopoCount |
VGG-16 |
69.2 |
68.3 |
70.1 |
5.7/39.1/72.2/85.7/87.3/89.7 |
63.3 |
2021--arXiv |
RDTM |
VGG-16 |
69.9 |
75.1 |
65.4 |
11.5/46.3/68.5/74.9/54.6/18.2 |
45.7 |
2021--arXiv |
SCALNet |
DLA-34 |
69.1 |
69.2 |
69.0 |
- |
- |
2021--TIP |
D2CNet |
VGG-16 |
70.0 |
74.1 |
66.2 |
11.3/50.2/67.8/74.5/69.5/76.5 |
58.3 |
2020--arXiv |
IIM |
VGG-16 |
73.2 |
77.9 |
69.2 |
10.1/44.1/70.7/82.4/83.0/61.4 |
58.7 |
2020--arXiv |
IIM |
HRNet |
76.2 |
81.3 |
71.7 |
12.0/46.0/73.2/85.5/86.7/64.3 |
61.3 |
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