Panoramic Video

Panoramic video research focuses on capturing and processing 360° video content, addressing challenges in stitching, rendering, and analysis inherent to its unique spherical geometry. Current research emphasizes developing robust algorithms and models, including neural light fields, graph convolutional networks, and diffusion models, to improve video stitching, object detection and tracking, and quality assessment in panoramic videos. These advancements are crucial for enhancing applications in virtual and augmented reality, autonomous driving, and robotics, where comprehensive scene understanding from a wide field of view is essential. The development of large-scale annotated datasets is also a key focus, enabling the training and evaluation of more sophisticated algorithms.