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Stereo vision is essential for many applications. Currently, thesynchronization of the streams coming from two cameras is done using mostlyhardware. A software-based synchronization method would reduce the cost, weightand size of the entire system and allow for more flexibility when building suchsystems. With this goal in mind, we present here a comparison of different deeplearning-based systems and prove that some are efficient and generalizableenough for such a task. This study paves the way to a production readysoftware-based video synchronization system.

Deep learning-based stereo camera multi-video synchronization