JOURNAL ARTICLE

On the Role of Scene Graphs in Image Captioning

Abstract

Scene graphs represent semantic information in images, which can help image captioning system to produce more descriptive outputs versus using only the image as context. Recent captioning approaches rely on ad-hoc approaches to obtain graphs for images. However, those graphs introduce noise and it is unclear the effect of parser errors on captioning accuracy. In this work, we investigate to what extent scene graphs can help image captioning. Our results show that a state-of-the-art scene graph parser can boost performance almost as much as the ground truth graphs, showing that the bottleneck currently resides more on the captioning models than on the performance of the scene graph parser.

Keywords:
Closed captioning Computer science Parsing Bottleneck Artificial intelligence Scene graph Image (mathematics) Natural language processing Context (archaeology) Graph Ground truth Theoretical computer science Rendering (computer graphics)

Metrics

29
Cited By
1.60
FWCI (Field Weighted Citation Impact)
25
Refs
0.87
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Multimodal Machine Learning Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Domain Adaptation and Few-Shot Learning
Physical Sciences →  Computer Science →  Artificial Intelligence

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