LCFCN - ECCV 2018

Where are the Blobs: Counting by Localization with Point Supervision

[Paper][Video]

Requirements

• Pytorch version 0.4 or higher.

Description

Given a test image, the trained model outputs blobs in the image, then counts the number of predicted blobs (see Figure below).

Running the saved models

1. Download the checkpoints,

bash checkpoints/download.sh

2. Output the saved results,

python main.py -m summary -e trancos

3. Re-evaluate the saved model,

python main.py -m test -e trancos

Training the models from scratch

To train the model,

python main.py -m train -e trancos

Benchmark

Method	Trancos	Pascal
ResFCN	3.39	0.31
Paper	3.32	0.31

Citation

If you find the code useful for your research, please cite:

@Article{laradji2018blobs,
    title={Where are the Blobs: Counting by Localization with Point Supervision},
    author={Laradji, Issam H and Rostamzadeh, Negar and Pinheiro, Pedro O and Vazquez, David and Schmidt, Mark},
    journal = {ECCV},
    year = {2018}
}