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Video super-resolution (VSR) is the process of generating high-resolution video frames from the given low-resolution video frames. Unlike single-image super-resolution (SISR) , the main goal is not only to restore more fine details while saving coarse ones, but also to preserve motion consistency.
Nvidia has also introduced Deep learning dynamic super resolution (DLDSR), a related and opposite technology where the graphics are rendered at a higher resolution, then downsampled to the native display resolution using an artificial intelligence-assisted downsampling algorithm to achieve higher image quality than rendering at native resolution.
Let's Enhance [1] is a Ukrainian start-up [2] which develops an online service driven by artificial intelligence which allows improving images and zooming them without losing quality. [3] According to the developers, [4] they used the super-resolution technology of machine learning. The neural network, trained on a large base of real ...
Then the resolution-independent version is rendered as a raster image at the desired resolution. This technique is used by Adobe Illustrator Live Trace, Inkscape, and several recent papers. [6] Scalable Vector Graphics are well suited to simple geometric images, while photographs do not fare well with vectorization due to their complexity.
An image scaled with nearest-neighbor scaling (left) and 2×SaI scaling (right) In computer graphics and digital imaging, image scaling refers to the resizing of a digital image. In video technology, the magnification of digital material is known as upscaling or resolution enhancement.
Firefly expanded its capabilities to Illustrator, Premiere Pro, and Express, particularly for generating photos, videos and audio to enhance or alter specific parts of the media. NVIDIA Picasso runs some Adobe Firefly models. [10] Google planned to use Firefly in Bard (now Gemini) as its AI image generator, but ended up using their own Imagen ...
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