A device may receive a first image . The device may process the first image to identify an object in the first image and a location of the object within the first image . The device may extract a second image from the first image based on the location of the object within the first image . The device may process the second image to determine at least one of a coarse - grained viewpoint estimate or a fine - grained view point estimate associated with the object . The device may determine an object viewpoint associated with the second vehicle based on the at least one of the coarse - grained viewpoint estimate or the fine - grained viewpoint estimate . The device may perform one or more actions based on the object viewpoint .
Systems and methods for utilizing a deep learning model to determine vehicle viewpoint estimations / Simone Magistri, Francesco Sambo, Douglas Coimbra De Andrade, Fabio SCHOEN, Matteo Simoncini, Luca Bravi, Stefano CAPRASECCA, Luca Kubin, Leonardo Taccari. - (2021).
Systems and methods for utilizing a deep learning model to determine vehicle viewpoint estimations
Simone Magistri;Fabio SCHOEN;Matteo Simoncini;Luca Bravi;Luca Kubin;
2021
Abstract
A device may receive a first image . The device may process the first image to identify an object in the first image and a location of the object within the first image . The device may extract a second image from the first image based on the location of the object within the first image . The device may process the second image to determine at least one of a coarse - grained viewpoint estimate or a fine - grained view point estimate associated with the object . The device may determine an object viewpoint associated with the second vehicle based on the at least one of the coarse - grained viewpoint estimate or the fine - grained viewpoint estimate . The device may perform one or more actions based on the object viewpoint .File | Dimensione | Formato | |
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