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Google introduces new text-to-video AI model mostly developed in Israel

Google introduces new text-to-video AI model mostly developed in Israel
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Omnimatte: Associating Objects and Their Effects in Video

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 water. Abstract Computer vision is increasingly effective at segmenting objects in images and videos; however, scene effects related to the objects shadows, reflections, generated smoke, etc are typically overlooked. Identifying such scene effects and associating them with the objects producing them is important for improving our fundamental understanding of visual scenes, and can also assis

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