Summary of Kale: An Artwork Image Captioning System Augmented with Heterogeneous Graph, by Yanbei Jiang et al.
KALE: An Artwork Image Captioning System Augmented with Heterogeneous Graph
by Yanbei Jiang, Krista A. Ehinger, Jey Han Lau
First submitted to arxiv on: 17 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a novel approach to image captioning, specifically for fine-art paintings. The goal is to generate descriptions that not only represent the visual content but also offer an in-depth interpretation of the artwork’s meaning. To tackle this challenge, the authors introduce KALE (Knowledge-Augmented vision-Language model for artwork Elaborations), which enhances existing vision-language models by incorporating artwork metadata as additional knowledge. KALE uses two approaches to incorporate metadata: direct textual input and a multimodal heterogeneous knowledge graph. The paper also introduces a new cross-modal alignment loss that maximizes the similarity between the image and its corresponding metadata. Experimental results show strong performance, particularly when evaluated with CIDEr, across several artwork datasets. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary KALE is an AI system that helps describe fine-art paintings in a way that’s both accurate and meaningful. It looks at pictures of artwork and uses extra information about each piece to create more detailed descriptions. This is helpful because people can interpret art in different ways, so the system needs to consider multiple perspectives. The researchers tested KALE on several sets of artwork images and found it did well compared to other state-of-the-art systems. |
Keywords
» Artificial intelligence » Alignment » Image captioning » Knowledge graph » Language model
