Assignment #5
Image Captioning
Overview
- In the previous assignments, we implemented multiple image classification tasks.
- In this assignment, you will design and train a neural network which combines CNN and RNN to process an input image, then output a sequence that describe the image.
- You are free to use pre-trained models like ResNet or LSTM as your backbone structure.
Image Captioning
Image captioning is an interdisciplinary research problem that stands between computer vision and natural language processing.
Flickr8k Dataset
• Flickr8k-Images-Captions
• CollectedbyAlexanderMamaev.
• Sentence-basedimagedescriptionandsearch • Consistingof8,091imagesthatareeach
paired with five different captions
A child in a pink dress is climbing up a set of stairs in an entry way .
Assignment #5 Dataset
8091 imags
captions
Your task
- We have code skeleton for you guys.
- https://colab.research.google.com/drive/1E96yjndJyBTAEEcgSth-
RyAVqd4H1WcW?usp=sharing
- Design a convolutional neural network to do image captioning.
- The images provided are of different resolutions. You’ll need to resize the images
- To get a high accuracy, you’ll need to experiment with different filter sizes, different number of layers, and other design principles discussed in class to figure out a network architecture that works best.
- You’ll also need to try data augmentation, dropout, batch normalization as well as different optimizers and other tricks to boost performance.
into a fixed size of your own choice.
Things you cannot do
• You cannot copy trained models from others.
• You cannot copy a whole page of code from the Internet.
Any violation will result in no points!
