Fusion Models for Improved Visual Captioning

no code implementations • 28 Oct 2020 • Marimuthu Kalimuthu, Aditya Mogadala, Marius Mosbach, Dietrich Klakow

Building on these recent developments, and with the aim of improving the quality of generated captions, the contribution of our work in this paper is two-fold: First, we propose a generic multimodal model fusion framework for caption generation as well as emendation where we utilize different fusion strategies to integrate a pretrained Auxiliary Language Model (AuxLM) within the traditional encoder-decoder visual captioning frameworks.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +5

A Competitive Deep Neural Network Approach for the ImageCLEFmed Caption 2020 Task

no code implementations • 11 Jul 2020 • Marimuthu Kalimuthu, Fabrizio Nunnari, Daniel Sonntag

The aim of ImageCLEFmed Caption task is to develop a system that automatically labels radiology images with relevant medical concepts.

Incremental Domain Adaptation for Neural Machine Translation in Low-Resource Settings

1 code implementation • WS 2019 • Marimuthu Kalimuthu, Michael Barz, Daniel Sonntag

We accelerate the fine-tuning process of the generic model to the target domain.

Active Learning Domain Adaptation +5

Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods

no code implementations • 22 Jul 2019 • Aditya Mogadala, Marimuthu Kalimuthu, Dietrich Klakow

Interest in Artificial Intelligence (AI) and its applications has seen unprecedented growth in the last few years.

BIG-bench Machine Learning