Summary of Bird’s-eye View to Street-view: a Survey, by Khawlah Bajbaa et al.
Bird’s-Eye View to Street-View: A Survey
by Khawlah Bajbaa, Muhammad Usman, Saeed Anwar, Ibrahim Radwan, Abdul Bais
First submitted to arxiv on: 14 May 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); 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 This paper reviews the state-of-the-art in synthesizing street-view images from their corresponding satellite images using deep learning techniques. The authors analyzed 20 recent research papers and found that novel approaches are needed to produce more realistic and accurate street-view images. They also highlight the importance of collecting more public datasets and developing specific evaluation metrics for this task. The study concludes that outdated techniques have limited the ability to generate detailed and diverse street-view images, highlighting the need for new methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how to combine satellite images with street-level views using computer science techniques. It’s like taking a picture from up high and matching it to what you would see on the ground. The authors looked at lots of other research papers and found that we need better ways to make these images match up. They also think we should have more pictures available for people to use, and better ways to check if the pictures are good or not. |
Keywords
» Artificial intelligence » Deep learning
