Artificial Intelligence and machine learning advancements have allowed researchers to build
detailed 3D models of real-world locations by using the reference data of thousands of tourists’ photos. The finished models have cleanly removed unwanted objects and even normalized lighting conditions.
The project and
associated paper are titled Neural Radiance Fields for Unconstrained Photo Collections and was
originally published in August of 2020. The project was
recently updated with even more examples of its application, a deep-dive video explanation of how the program works, and published findings that take the idea of converting 2D to 3D a step further.
To recap, researchers used a photo tourism data set of thousands of images to produce highly-detailed models of iconic locations.
“You can see that we are able to produce high-quality renderings of novel views of these scenes using only unstructured image collections as input,” the researchers say.
“Getting good results from uncontrolled internet photos can a challenging task because these images have likely been taken at different times, ” the researchers explain. “So the weather might change or the sun might move. They can have different types of post-processing applied to them. Also, people generally don’t take photos of landmarks in isolation: there might be people posing for the camera, or pedestrians or cars moving through the scene.”
petapixel.com
