ADC-image-captioning

Code for our paper: A Novel Actor Dual-Critic Model for Image Captioning, ICPR 2020
Ruchika Chavhan, Biplab Banerjee, Xiao Xiang Zhu, Subhasis Chaudhuri

Datasets

1. Remote Sensing Image Captioning Dataset (RSICD)
   
2. UC-Merced Captioning Dataset
   Please make sure your data contains images and a json file containing captions corresponding to each image.

Methodology

Training

Step 1: Build vocabulary

python vocab_build.py --caption_path <path to json file> --vocab_path <path to save the vocab file>

Step 2: Train Model

To load a pretrained Actor and Value Network model and train

python train.py --data_path <path to images> --json_path <path to json file> --load_pretrained --actor_pretrained <path to actor model> --critic_pretrained <path to critic model>

To train from scratch

python train.py --data_path <path to images> --json_path <path to json file>

Citation

If you find this work useful, please cite our paper,

@inproceedings{chavhan2020novel,
author    = {Ruchika Chavhan and Biplab Banerjee and Xiao Xiang Zhu and Subhasis Chaudhuri},
title     = {A Novel Actor Dual-Critic Model for Remote Sensing Image Captioning},
booktitle = {International Conference on Pattern Recognition (ICPR)},
year      = {2020}
}

References

A significant part of this code has been adapted from the code from Actor-Critic Sequence Training for Image Captioning