English

Hyperparameter Analysis for Image Captioning

Computer Vision and Pattern Recognition 2020-06-22 v1 Machine Learning

Abstract

In this paper, we perform a thorough sensitivity analysis on state-of-the-art image captioning approaches using two different architectures: CNN+LSTM and CNN+Transformer. Experiments were carried out using the Flickr8k dataset. The biggest takeaway from the experiments is that fine-tuning the CNN encoder outperforms the baseline and all other experiments carried out for both architectures.

Keywords

Cite

@article{arxiv.2006.10923,
  title  = {Hyperparameter Analysis for Image Captioning},
  author = {Amish Patel and Aravind Varier},
  journal= {arXiv preprint arXiv:2006.10923},
  year   = {2020}
}

Comments

10 pages, 9 figures, and 7 tables

R2 v1 2026-06-23T16:27:14.579Z