CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting
論文地址：https://arxiv.org/pdf/1707.09605.pdf 代碼地址：https://github.com/svishwa/crowdcount-cascaded-mtl Abstract 提出了一種新的端對端的級聯神經網絡同時學習人羣數量分類以及密度圖估計； 將人羣數量分成不同的組別等價於粗略地對人羣數目進行估計，之後其可以作爲一個高水平的先驗信息加入到密度圖估計的神
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相關文章
- 1. 人羣分析--Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks
- 2. 論文解讀《Density-Aware Multi-Task Learning for Crowd Counting》IEEE Transactions on MultiMedia2020
- 3. Segmentation Guided Attention Network for Crowd Counting via Curriculum Learning
- 4. 人羣計數：SFCN--Learning from Synthetic Data for Crowd Counting in the Wild
- 5. Geometric and Physical Constraints for Head Plane Crowd Density Estimation in Videos
- 6. 論文《ResnetCrowd: A Residual Deep Learning Architecture for Crowd Counting, Violent Behaviour Detecti》
- 7. [論文筆記 CVPR2020]Attention Scaling for Crowd Counting
- 8. Crowd Counting（人羣計數）
- 9. 人羣計數論文筆記之Density-Aware Multi-Task Learning for Crowd Counting
- 10. 論文解讀《Almost Unsupervised Learning for Dense Crowd Counting》AAAI2019