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Researchers at MIT and elsewhere have demonstrated a novel technique that vastly increases the speed of rendering 3D scenes from images by using a neural network to reconstruct the 360-degree light field of the underlying 3D scene.
Omnimatte: Associating Objects and Their Effects in Video We pose a novel problem: automatically associating subjects in videos with ‘effects’ related to them in the scene. Given an input video (top) and rough masks of subjects of interest (middle), our method estimates an omnimatte – an alpha matte and foreground color that includes the subject itself along with all scene elements associated with it (bottom). The associated elements can be other objects attached to the subject or moving with it, or complex effects such as shadows, reflections, smoke, or ripples the subject creates in ...
Table Of Contents Yesterday some extraordinary new work in neural image synthesis caught the attention and the imagination of the internet, as Intel researchers revealed a new method for enhancing the realism of synthetic images. The system, as demonstrated in a video from Intel, intervenes directly into the image pipeline for the Grand Theft Auto V video game, and automatically enhances the images through an image synthesis algorithm trained on a convolutional neural network (CNN), using real world imagery from the Mapillary dataset, and swapping out the less realistic lighting and texturi...