论文理解Leveraging Unlabeled Data for Crowd Counting by Learning to Rank
论文：Leveraging Unlabeled Data for Crowd Counting by Learning to Rank 作者：Xialei Liu、Joost van de Weijer、Andrew D. Bagdanov Abstract novel approach:文中提出一种新方法，在learning-to-rank框架中利用大量可得的无标签人群图像。 main idea
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相关文章
- 1. 论文理解《Learning from Synthetic Data for Crowd Counting in the Wild》
- 2. 论文解读《Almost Unsupervised Learning for Dense Crowd Counting》AAAI2019
- 3. 【论文笔记】Learning from Synthetic Data for Crowd Counting in the Wild
- 4. 论文解读《Density-Aware Multi-Task Learning for Crowd Counting》IEEE Transactions on MultiMedia2020
- 5. 论文理解《Body Structure Aware Deep Crowd Counting》
- 6. [论文笔记 ECCV2020] Learning to Count in the Crowd from Limited Labeled Data
- 7. 论文《ResnetCrowd: A Residual Deep Learning Architecture for Crowd Counting, Violent Behaviour Detecti》
- 8. 人群计数：SFCN--Learning from Synthetic Data for Crowd Counting in the Wild
- 9. 论文解读《CrowdNet: A Deep Convolutional Network for Dense Crowd Counting》ACMM-MM2016
- 10. [论文笔记 CVPR2020]Attention Scaling for Crowd Counting