本标准定义了基于深度学习的视觉内容分析和体验质量（QoE）评估指标，这是基于心理物理研究的三维（3D）内容的QoE和视觉舒适性评估标准（IEEE Std 3333.1.1）和三维和超高清（UHD）内容的感知质量评估标准（IEEE Std 3333.1.2）的扩展。范围包括以下内容。*用于QoE评估的深度学习模型（多层感知器、卷积神经网络、深度生成模型）*来自高清（HD）、超高清（UHD）、3D、高动态范围（HDR）、虚拟现实（VR）和混合现实（MR）内容的视觉体验深度指标*临床（脑电图（EEG）、心电图（ECG）、眼电图（EOG）的深度分析，等等）和心理物理（主观测试和模拟器疾病问卷（SSQ））数据，用于QoE评估*视觉内容的深度个性化偏好评估*必要时建立图像和视频数据库，用于性能基准测试

This standard defines deep learning-based metrics of content analysis and quality of experience (QoE) assessment for visual contents, which is an extension of the standard for the QoE and visual-comfort assessments of three-dimensional (3D) contents based on psychophysical studies (IEEE Std 3333.1.1) and the standard for the perceptual quality assessment of 3D and ultra-high definition (UHD) contents (IEEE Std 3333.1.2). The scope covers the following. * Deep learning models for QoE assessment (multilayer perceptrons, convolutional neural networks, deep generative models) * Deep metrics of visual experience from High Definition (HD), UHD, 3D, High Dynamic Range (HDR), Virtual Reality (VR) and Mixed Reality (MR) contents * Deep analysis of clinical (electroencephalogram (EEG), electrocardiogram (ECG), electrooculography (EOG), and so on) and psychophysical (subjective test and simulator sickness questionnaire (SSQ)) data for QoE assessment * Deep personalized preference assessment of visual contents * Building image and video databases for performance benchmarking purpose if necessary