Summary of Ceia: Clip-based Event-image Alignment For Open-world Event-based Understanding, by Wenhao Xu et al.
CEIA: CLIP-Based Event-Image Alignment for Open-World Event-Based Understanding
by Wenhao Xu, Wenming Weng, Yueyi Zhang, Zhiwei Xiong
First submitted to arxiv on: 9 Jul 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 introduces CEIA, an innovative framework for open-world event-based understanding that addresses the challenge of training a large event-text model due to the scarcity of paired event-text data. Instead of directly aligning event and text data, CEIA learns to align event and image data as an alternative, leveraging rich event-image datasets through contrastive learning. This allows natural alignment of event and text data via using image data as a bridge. CEIA offers two key advantages: it enables the use of existing event-image datasets to overcome the shortage of large-scale event-text datasets, and it boosts performance with more training data, ensuring scalable capability. The framework is evaluated through various event-based multi-modal applications, including object recognition, event-image retrieval, event-text retrieval, and domain adaptation, demonstrating CEIA’s zero-shot superiority over existing methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary CEIA is a new way to understand events by using images and text together. Right now, it’s hard to train computers to recognize events because we don’t have enough data that shows how events relate to words and pictures. To fix this, the researchers created CEIA, which learns to connect event information with image information instead. This helps bridge the gap between words and pictures, allowing for better understanding of events. CEIA has two main benefits: it allows us to use existing data about images and events to train computers, and it makes computers more accurate and efficient as they learn from more data. |
Keywords
» Artificial intelligence » Alignment » Domain adaptation » Multi modal » Zero shot
