Neural Radiance Fields (NeRFs) have demonstrated the remarkable potential of neural networks to capture the intricacies of 3D objects. By encoding the shape and color information within neural network weights, NeRFs excel at producing strikingly sharp novel views of 3D objects. Recently, numerous generalizations of NeRFs utilizing generative models have emerged, expanding its versatility. In contrast, Gaussian Splatting (GS) offers a similar render quality with faster training and inference as it does not need neural networks to work. It encodes information about the 3D objects in the set of Gaussian distributions that can be rendered in 3D similarly to classical meshes. The grant’s goal is: Effective rendering of 3D objects using Gaussian Splatting in an Augmented Reality environment.

The execution of the project occurred under the FIRST TEAM FENG programme of the Foundation for Polish Science, with co-financing from the European Union through the European Regional Development Fund. The project received funding amounting to PLN 3 129 800.