June 6, 2024, 4:49 a.m. | Tobias Fischer, Jonas Kulhanek, Samuel Rota Bul\`o, Lorenzo Porzi, Marc Pollefeys, Peter Kontschieder

cs.CV updates on arXiv.org arxiv.org

arXiv:2406.03175v1 Announce Type: new
Abstract: We present an efficient neural 3D scene representation for novel-view synthesis (NVS) in large-scale, dynamic urban areas. Existing works are not well suited for applications like mixed-reality or closed-loop simulation due to their limited visual quality and non-interactive rendering speeds. Recently, rasterization-based approaches have achieved high-quality NVS at impressive speeds. However, these methods are limited to small-scale, homogeneous data, i.e. they cannot handle severe appearance and geometry variations due to weather, season, and lighting and …

abstract applications arxiv cs.cv dynamic fields interactive loop mixed novel quality reality rendering representation scale simulation synthesis type urban view visual

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