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Nvidia VDPAU Feature Sets [32] are different hardware generations of GPU's supporting different levels of (Nvidia PureVideo) hardware decoding capabilities. For feature sets A, B and C, the maximum video width and height are 2048 pixels , minimum width and height 48 pixels, and all codecs are currently limited to a maximum of 8192 macroblocks ...
Nvidia NVDEC (formerly known as NVCUVID [1]) is a feature in its graphics cards that performs video decoding, offloading this compute-intensive task from the CPU. [2] NVDEC is a successor of PureVideo and is available in Kepler and later NVIDIA GPUs. It is accompanied by NVENC for video encoding in Nvidia's Video Codec SDK. [2]
Nvidia NVENC (short for Nvidia Encoder) [1] is a feature in Nvidia graphics cards that performs video encoding, offloading this compute-intensive task from the CPU to a dedicated part of the GPU. It was introduced with the Kepler -based GeForce 600 series in March 2012 (GT 610, GT620 and GT630 is Fermi Architecture).
On March 14, 2013, Ittiam Systems Announces Availability and Software Licensing of HEVC (H.265) Video Encoder and Decoder for Professional, Enterprise and Consumer Digital Media Markets. The HEVC Encoder is a software implementation on Intel x86 based platforms, capable of High Definition (HD) broadcast quality video encoding.
Nvidia VDPAU Feature Sets [18] are different hardware generations of Nvidia GPU's supporting different levels of hardware decoding capabilities. For feature sets A, B and C, the maximum video width and height are 2048 pixels , minimum width and height 48 pixels, and all codecs are currently limited to a maximum of 8192 macroblocks (8190 for VC ...
4096 × 2160, referred to as DCI 4K, Cinema 4K [58] or 4K × 2K, is the resolution used by the 4K container format defined by the Digital Cinema Initiatives Digital Cinema System Specification, a prominent standard in the cinema industry. This resolution has an aspect ratio of 256:135 (1.8 962:1), and 8,847,360 total pixels. [11]
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.
The data DLSS 2.0 collects includes: the raw low-resolution input, motion vectors, depth buffers, and exposure / brightness information. [14] It can also be used as a simpler TAA implementation where the image is rendered at 100% resolution, rather than being upsampled by DLSS, Nvidia brands this as DLAA (deep learning anti-aliasing). [26]