NeRF - Neural Radiance Fields for 3reCapSL (WiSe 2022/23)
Neural radiance fields (NeRF) are an emerging technology for photorealistic view synthesis on 3D sceneries. Unlike other approaches, the 3D geometry of the scene is not explicity modelled and stored, rather implicitly encoded into a multi-layer perceptron (MLP). NeRFs have produced impressive results for a number of applications. In this project, the applicability of NeRFs in the context of our 3reCapSL photo dome is explored.
For that purpose a (1) 3D reconstruction pipeline is to be scripted, (2) a deep understanding and solid implementation skill on NeRFs is developed, and (3) extensions on NeRFs for recognition tasks are to be explored.
Supervised by Jan Frederick Eick, Paul Debus, and Christian Benz.