Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation (CVPR 2021)

Overview

Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation

Input Image Initial CAM Successive Maps with adversarial climbing
a b c

The implementation of Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation, Jungbeom Lee, Eunji Kim, and Sungroh Yoon, CVPR 2021. [paper]

Installation

  • We kindly refer to the offical implementation of IRN.
  • This repository is tested on Ubuntu 18.04, with Python 3.6, PyTorch 1.4, pydensecrf, scipy, chaniercv, imageio, and opencv-python.

Usage

Step 1. Prepare Dataset

  • Download PASCAL VOC 2012 benchmark: Download.

Step 2. Prepare pre-trained classifier

  • Pre-trained model used in this paper: Download.
  • You can also train your own classifiers following IRN.

Step 3. Obtain the pseudo ground-truth masks for PASCAL VOC train_aug images and evaluate them

bash get_mask_quality.sh

Step 4. Train a semantic segmentation network

Acknowledgment

This code is heavily borrowed from IRN, thanks jiwoon-ahn!

Owner
Jungbeom Lee
Jungbeom Lee
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