Zero-BEV: Zero-shot Projection of Any First-Person Modality to BEV Maps

arXiv:2402.13848v1 Announce Type: new
Abstract: Bird's-eye view (BEV) maps are an important geometrically structured representation widely used in robotics, in particular self-driving vehicles and terrestrial robots. Existing algorithms either require depth information for the geometric projection, which is not always reliably available, or are trained end-to-end in a fully supervised way to map visual first-person observations to BEV representation, and are therefore restricted to the output modality they have been trained for. In contrast, we propose a new model capable …

abstract algorithms arxiv bird cs.cv cs.ro driving information maps person projection representation robotics robots self-driving self-driving vehicles type vehicles view zero-shot