3 accepted papers
LiDAR depth cameras are widely used for accurate depth measurement in various applications. However, when multiple cameras operate simultaneously, mutual interference causes artifacts in the captured depth data, which existing image restoration methods struggle to handle. In this paper, we propose D…
LiDAR depth cameras are widely used for accurate depth measurement in various applications. However, when multiple cameras operate simultaneously, mutual interference causes artifacts in the captured depth data, which existing image restoration methods struggle to handle. In this paper, we propose D
As concerns regarding privacy in deep learning continue to grow, individuals are increasingly apprehensive about the potential exploitation of their personal knowledge in trained models. Despite several research efforts to address this, they often fail to consider the real-world demand from users fo…