Panoramic Video Quality Assessment Based on Non-Local Spherical CNN

Panoramic video and stereoscopic panoramic are essential carriers of virtual reality content, so it is very crucial to establish their quality assessment models for the standardization industry. However, challenging evaluate at present. One reason that spatial information warped due projection process, conventional (VQA) method difficult deal with this problem. Another traditional VQA problematic capture complex global time in video. In response above questions, paper presents an end-to-end neural network model Compared other methods, our proposed combines spherical convolutional networks (CNN) non-local networks, which can effectively extract spatiotemporal We two databases, VRQ-TJU VR-VQA48. Experiments show effectiveness different modules method, outperforms state-of-the-art related methods.