In this PhD project, you will investigate neural 3D scene representations, including neural radiance fields, Gaussian splatting, and implicit occupancy models, and adapt them to the unique challenges of in-cabin perception. * You will leverage this asymmetry as an advantage by using the known cabin geometry as built-in supervision and by incorporating modern 3D-aware diffusion models as learned priors. * Your work will combine fundamental research in 3D computer vision and generative modeling with the practical goal of making vehicles safer for everyone on board. o good programming skills in Python and solid foundations in computer vision and 3D geometry, including camera models, projective geometry, and multi-view constraints - o familiarity with 3D scene representations (e.g., NeRF, Gaussian splatting, implicit/occupancy networks) or depth/3D estimation methods is strongly preferred
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