VieCap4H-VLSP 2021: ObjectAoA – Enhancing performance of Object Relation Transformer with Attention on Attention for Vietnamese image captioning

11/10/2022
by   Nghia Hieu Nguyen, et al.
0

Image captioning is currently a challenging task that requires the ability to both understand visual information and use human language to describe this visual information in the image. In this paper, we propose an efficient way to improve the image understanding ability of transformer-based method by extending Object Relation Transformer architecture with Attention on Attention mechanism. Experiments on the VieCap4H dataset show that our proposed method significantly outperforms its original structure on both the public test and private test of the Image Captioning shared task held by VLSP.

READ FULL TEXT

page 10

page 11

page 12

page 13

page 14

research
02/11/2022

ACORT: A Compact Object Relation Transformer for Parameter Efficient Image Captioning

Recent research that applies Transformer-based architectures to image ca...
research
04/29/2020

Image Captioning through Image Transformer

Automatic captioning of images is a task that combines the challenges of...
research
11/10/2019

Can Neural Image Captioning be Controlled via Forced Attention?

Learned dynamic weighting of the conditioning signal (attention) has bee...
research
02/11/2023

See Your Heart: Psychological states Interpretation through Visual Creations

In psychoanalysis, generating interpretations to one's psychological sta...
research
07/29/2021

ReFormer: The Relational Transformer for Image Captioning

Image captioning is shown to be able to achieve a better performance by ...
research
10/04/2021

Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning

Explaining an image with missing or non-existent objects is known as obj...
research
01/04/2020

Understanding Image Captioning Models beyond Visualizing Attention

This paper explains predictions of image captioning models with attentio...

Please sign up or login with your details

Forgot password? Click here to reset