Multimodal Differential Network for Visual Question Generation

08/12/2018
by   Badri N. Patro, et al.
0

Generating natural questions from an image is a semantic task that requires using visual and language modality to learn multimodal representations. Images can have multiple visual and language contexts that are relevant for generating questions namely places, captions, and tags. In this paper, we propose the use of exemplars for obtaining the relevant context. We obtain this by using a Multimodal Differential Network to produce natural and engaging questions. The generated questions show a remarkable similarity to the natural questions as validated by a human study. Further, we observe that the proposed approach substantially improves over state-of-the-art benchmarks on the quantitative metrics (BLEU, METEOR, ROUGE, and CIDEr).

READ FULL TEXT
research
01/23/2020

Deep Bayesian Network for Visual Question Generation

Generating natural questions from an image is a semantic task that requi...
research
07/30/2023

Distractor generation for multiple-choice questions with predictive prompting and large language models

Large Language Models (LLMs) such as ChatGPT have demonstrated remarkabl...
research
10/08/2019

Generating Highly Relevant Questions

The neural seq2seq based question generation (QG) is prone to generating...
research
11/18/2014

From Captions to Visual Concepts and Back

This paper presents a novel approach for automatically generating image ...
research
04/13/2015

Joint Learning of Distributed Representations for Images and Texts

This technical report provides extra details of the deep multimodal simi...
research
11/14/2022

Multi-VQG: Generating Engaging Questions for Multiple Images

Generating engaging content has drawn much recent attention in the NLP c...
research
05/15/2019

VICSOM: VIsual Clues from SOcial Media for psychological assessment

Sharing multimodal information (typically images, videos or text) in Soc...

Please sign up or login with your details

Forgot password? Click here to reset