Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd Counting

ICCV 2021 Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd Counting

Baseline of DKPNet is available.

Currently, only code of DKPNet-baseline is released.

In fact, MSE in our paper is equivalent to RMSE in academic papers. Please use the word RMSE instead of MSE when refering to the corresponding numerical values in our paper. We are sorry for the mistake and can do nothing to corret it after the camera-ready version deadline.

Download the datasets ShanghaiTech A, ShanghaiTech B, UCF-QNRF and NWPU Then generate the density maps via generate_density_map_perfect_names_SHAB_QNRF_NWPU_JHU.py. After that, create a folder named JSTL_large_4_dataset, and directly copy all the processed data in JSTL_large_4_dataset.

The tree of the folder should be: