论文解读《Crowd Density Estimation Using Fusion of Multi-Layer Features》T-ITS2020

时间 2020-12-30

标签 crowd counting paper 深度学习繁體版

原文原文链接

Crowd Density Estimation Using Fusion of Multi-Layer Features Xinghao Ding , Member , IEEE, Fujin He, Zhirui Lin, Y u Wang, Huimin Guo, and Y ue Huang Abstract: 人群统计在视频监控、交通监控、公共安全、城市规划等诸多工作中都具有重要意义，是

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1. 【论文浅读】《Generating High-Quality Crowd Density Maps Using Contextual Pyramid CNNs》
2. 论文阅读:High-Precision Depth Estimation Using Uncalibrated LiDAR and Stereo Fusion
3. 论文解读《Density-Aware Multi-Task Learning for Crowd Counting》IEEE Transactions on MultiMedia2020
4. 人群密度估计--Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs
5. CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting
6. 论文解读《Crowd Counting via Multi-layer Regression》ACM-MM2019
7. 论文阅读Bayesian Loss for Crowd Count Estimation with Point Supervision
8. 论文解读《Almost Unsupervised Learning for Dense Crowd Counting》AAAI2019
9. 论文解读《CrowdNet: A Deep Convolutional Network for Dense Crowd Counting》ACMM-MM2016
10. 【论文阅读】3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for

>>更多相关文章<<