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Tensorflow implementation of "Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization"[ICCV 2017]

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Hide and Seek - Weakly Supervised Object Detector

Implementation of "Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization" https://arxiv.org/abs/1704.04232


Download data

Download data with the script below. The script download tiny-imagenet data and transform to pickle and tfrecord. The pickle include datasets and meta information of label dictionary. The tfrecord contains datasets; train dataset, valid dataset, test dataset.

python3 download_data.py

Requirements

  • python3.4
  • pip3
  • python packages - requirements.txt
  • tensorflow 1.4

How to train

$ jupyter lab

and open train_HaS.ipynb

or 

use snippet_train_model.py

How to test

$ jupyter lab

and open load_and_test.ipynb

Architecture

Alt text

Hide Patches Example

Alt text

Result Sample

  • Green bounding box is prediction
  • Red bounding box is ground truth

Alt text

Alt text

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Tensorflow implementation of "Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization"[ICCV 2017]

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