Summary of Ifcap: Image-like Retrieval and Frequency-based Entity Filtering For Zero-shot Captioning, by Soeun Lee et al.
IFCap: Image-like Retrieval and Frequency-based Entity Filtering for Zero-shot Captioning
by Soeun Lee, Si-Woo Kim, Taewhan Kim, Dong-Jin Kim
First submitted to arxiv on: 26 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)
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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 proposed method, IFCap, is a novel approach that bridges the modality gap between text-only training and image-based inference in image captioning. It combines two key components: Image-like Retrieval, which aligns text features with visually relevant features, and Fusion Module, which integrates retrieved captions with input features. Additionally, Frequency-based Entity Filtering enhances caption quality. The unified framework outperforms state-of-the-art methods by a significant margin in both image and video captioning tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Image captioning has become more accurate thanks to new ways of training models without paired images and text data. A team of researchers has come up with an innovative solution that helps models understand the difference between using text during learning and seeing images later. They call this approach Image-like Retrieval, which connects what words mean to what we see in pictures. Another important part is a Fusion Module that combines these connections with other information about the image. The team also introduced a way to remove unnecessary details from captions, making them more accurate and better. This combined method, called IFCap, beats current best methods for describing both images and videos. |
Keywords
» Artificial intelligence » Image captioning » Inference
