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Implementation of ISIM: Iterative Self-Improved Model for Weakly Supervised Segmentation

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ISIM

The official implementation of "ISIM: Iterative Self-Improved Model for Weakly Supervised Segmentation".

Citation

  • In Review for IJCV
  • Please cite our paper if the code is helpful to your research. arxiv

Overview

Overall architecture


Prerequisite

  • Python 3.7.11, PyTorch 1.7.0, and more in requirements.txt
  • pydensecrf
  • CUDA 11.5
  • RTX 3090 GPU, RTX 2080 GPU (x4)

Usage

Install python dependencies

pip install -r requirements.txt
pip install git+https://github.com/lucasb-eyer/pydensecrf.git

Download PASCAL VOC 2012 devkit

Follow instructions in https://host.robots.ox.ac.uk/pascal/VOC/voc2012/#devkit

1. Run the experiments

./scripts/experiments.sh

2. Get prediction results for the trained models

./scripts/infer_experiments.sh

3. Evaluate the predictions

./scripts/eval_experiments.sh

5. Results

Methods val mIoU test mIoU
ISIM with ResNet-101 70.51 71.45
ISIM with ResNeSt-200 74.90 74.98

Qualitative segmentation results on the PASCAL VOC 2012 validation set.

Qualitative Results

6. Provide the trained weights and training logs

  • Release the final masks by our models. (SOON)
Model val test
DeepLabv3+ ResNet-101 val.tgz test.tgz
DeepLabv3+ ResNeSt-200 val.tgz test.tgz

For any issues, please contact Cenk Bircanoglu, [email protected]

7. Notes

  • In MID-2021, Project started.
  • 15 Nov 2021, paper submitted to IJCV.
  • On 21 January 2022, Got a refusal from IJCV.
  • On 25 January 2022, Cenk Bircanoglu got the Covid-19 Vaccine and had severe health problems.
  • On 20 November 2022, Health issues were relatively possible to manage, and we decided to continue this project.
  • On 21 November 2022, Found out RecurSeed and EdgePredictMix. A similar idea (honestly, with a lot of improvements) has already been published.
  • On 23 November 2022, Decided to put the paper to arxiv, share the code, note the project in history, and start from scratch with a new idea.

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