論文解讀《Crowd Density Estimation Using Fusion of Multi-Layer Features》T-ITS2020
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: 人羣統計在視頻監控、交通監控、公共安全、城市規劃等諸多工作中都具有重要意義，是
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相關文章
- 1. 【論文淺讀】《Generating High-Quality Crowd Density Maps Using Contextual Pyramid CNNs》
- 2. 論文閱讀:High-Precision Depth Estimation Using Uncalibrated LiDAR and Stereo Fusion
- 3. 論文解讀《Density-Aware Multi-Task Learning for Crowd Counting》IEEE Transactions on MultiMedia2020
- 4. 人羣密度估計--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. 論文解讀《Crowd Counting via Multi-layer Regression》ACM-MM2019
- 7. 論文閱讀Bayesian Loss for Crowd Count Estimation with Point Supervision
- 8. 論文解讀《Almost Unsupervised Learning for Dense Crowd Counting》AAAI2019
- 9. 論文解讀《CrowdNet: A Deep Convolutional Network for Dense Crowd Counting》ACMM-MM2016
- 10. 【論文閱讀】3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for