Abstract: Apparatuses, systems, and techniques to facilitate understanding of media content using neural networks to adjust playback speed and volume based on environmental and other factors. In at least one embodiment, playback of media content is slowed down or sped up if audio associated with said media content is difficult to understand based on background noise, accent, difficulty of material, as well as other factors that decrease understandability of media content.

Abstract: Systems and methods for collaborative illumination estimation for mobile mixed-reality devices are provided. Embodiments described herein compose an illumination estimate using video data capturing an environment which includes a reflective object, such as a light probe. Radiance samples are computed from light reflections from the reflective object, which are then interpolated to compose a realistic estimation of physical lighting of the environment. Robust illumination estimation is provided in a computationally efficient manner, supplying real-time updates to facilitate integration with augmented reality (AR) systems and other image processing applications. The computational efficiency of this approach allows for implementation in lower-resource environments, such as mobile devices. In some examples, multiple devices can collaborate to capture the environment from different viewpoints and enhance realism and fidelity in their illumination estimates.

Abstract: Systems and methods for collaborative illumination estimation for mobile mixed-reality devices are provided. Embodiments described herein compose an illumination estimate using video data capturing an environment which includes a reflective object, such as a light probe. Radiance samples are computed from light reflections from the reflective object, which are then interpolated to compose a realistic estimation of physical lighting of the environment. Robust illumination estimation is provided in a computationally efficient manner, supplying real-time updates to facilitate integration with augmented reality (AR) systems and other image processing applications. The computational efficiency of this approach allows for implementation in lower-resource environments, such as mobile devices. In some examples, multiple devices can collaborate to capture the environment from different viewpoints and enhance realism and fidelity in their illumination estimates.