Stereo Video

Stereo video research focuses on creating and processing realistic three-dimensional video content, aiming for high-quality, efficient, and temporally consistent results. Current efforts concentrate on developing advanced deep learning models, often employing transformer architectures or novel convolutional networks, to address challenges like disparity estimation, video compression, and view synthesis from single-view inputs. These advancements are driving improvements in applications such as virtual and augmented reality, autonomous driving, and high-speed, high-resolution 3D video capture, impacting both the scientific understanding of visual perception and the development of immersive technologies.