Abstract: Digital content stylization techniques are described that leverage a neural photofinisher to generate stylized digital images. In one example, the neural photofinisher is implemented as part of a stylization system to train a neural network to perform digital image style transfer operations using reference digital content as training data. The training includes calculating a style loss term that identifies a particular visual style of the reference digital content. Once trained, the stylization system receives a digital image and generates a feature map of a scene depicted by the digital image. Based on the feature map as well as the style loss, the stylization system determines visual parameter values to apply to the digital image to incorporate a visual appearance of the particular visual style. The stylization system generates the stylized digital image by applying the visual parameter values to the digital image automatically and without user intervention.

Abstract: Disclosed herein is methods and systems for providing different views to a viewer. One particular embodiment includes a method including providing, to a neural network, a plurality of 2D images of a 3D object. The neural network may include a signed distance function based sinusoidal representation network. The method may further include obtaining a neural model of a shape of the object by obtaining a zero-level set of the signed distance function; and modeling an appearance of the object using a spatially varying emission function. In some embodiments, the neural model may be converted into a triangular mesh representing the object which may be used to render multiple view-dependent images representative of the 3D object.

Abstract: Disclosed herein is methods and systems for providing different views to a viewer. One particular embodiment includes a method including providing, to a neural network, a plurality of 2D images of a 3D object. The neural network may include a signed distance function based sinusoidal representation network. The method may further include obtaining a neural model of a shape of the object by obtaining a zero-level set of the signed distance function; and modeling an appearance of the object using a spatially varying emission function. In some embodiments, the neural model may be converted into a triangular mesh representing the object which may be used to render multiple view-dependent images representative of the 3D object.