立体视觉是计算机视觉中一个日益增长的主题，这是因为该技术为开发现代解决方案（例如虚拟和增强现实应用程序）提供了无数的机会和应用程序。为了增强用户在三维虚拟环境中的体验，运动视差估计是实现此目标的一种有前途的技术。..

Parallax Motion Effect Generation Through Instance Segmentation And Depth Estimation

Stereo vision is a growing topic in computer vision due to the innumerable opportunities and applications this technology offers for the development of modern solutions, such as virtual and augmented reality applications. To enhance the user's experience in three-dimensional virtual environments, the motion parallax estimation is a promising technique to achieve this objective.In this paper, we propose an algorithm for generating parallax motion effects from a single image, taking advantage of state-of-the-art instance segmentation and depth estimation approaches. This work also presents a comparison against such algorithms to investigate the trade-off between efficiency and quality of the parallax motion effects, taking into consideration a multi-task learning network capable of estimating instance segmentation and depth estimation at once. Experimental results and visual quality assessment indicate that the PyD-Net network (depth estimation) combined with Mask R-CNN or FBNet networks (instance segmentation) can produce parallax motion effects with good visual quality.