Cornell Unveils WildCAT3D for Diverse 3D Scenes
Cornell University researchers have introduced a new method to create lifelike 3D environments from everyday photos. The framework, called WildCAT3D, uses novel view synthesis, a technique that generates new views of a scene from a single photo. WildCAT3D is designed to work with large collections of publicly available images, including tourist photos and images taken in various weather, lighting, and seasonal conditions.
The research team, which includes Cornell Tech assistant professor Hadar Averbuch-Elor, presented their work on December 4 at the Conference and Workshop on Neural Information Processing. Their approach addresses a key challenge in 3D image-generation technology: existing systems usually learn from small, carefully chosen datasets that do not represent the wide variety of images available on the internet. By training computers on more diverse collections, the new framework opens up potential uses in gaming, virtual tourism, historical preservation, and immersive mapping.
Source: Cornell University
Source Type: College
Source Location: Ithaca
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