Add badges and links

README.md

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 [<img src='https://s3.amazonaws.com/drivendata-public-assets/logo-white-blue.png' width='600'>](https://www.drivendata.org/)
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-![Banner Image](https://drivendata-public-assets.s3.amazonaws.com/geopose-homepage.png)
+[![Banner Image](https://drivendata-public-assets.s3.amazonaws.com/geopose-homepage.png)](https://www.drivendata.org/competitions/78/overhead-geopose-challenge/)
 <figcaption>Images shown are from the public <a href="https://ieee-dataport.org/open-access/urban-semantic-3d-dataset">Urban Semantic 3D Dataset</a>, provided courtesy of DigitalGlobe</figcaption>
 
 # Overhead Geopose Challenge
 
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.8329905.svg)](https://doi.org/10.5281/zenodo.8329905)
+[![Overhead Geopose Challenge](https://img.shields.io/badge/DrivenData-Overhead%20Geopose%20Challenge-white?logo=data:image/png;base64,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)](https://www.drivendata.org/competitions/78/overhead-geopose-challenge/)
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 ## Goal of the Competition
 
 Overhead satellite imagery provides critical, time-sensitive information for use in arenas such as disaster response, navigation, and security. Most current methods for using aerial imagery assume images are taken from directly overhead, known as *near-nadir*. However, the first images available are often taken from an angle — they are *oblique*. Effects from these camera orientations complicate useful tasks such as change detection, vision-aided navigation, and map alignment.