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  2. Anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Anti-aliasing

    Deep learning anti-aliasing (DLAA), a type of spatial and temporal anti-aliasing method relying on dedicated tensor core processors Deep learning super sampling (DLSS), a family of real-time deep learning image enhancement and upscaling technologies developed by Nvidia that are available in a number of video games.

  3. Multisample anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Multisample_anti-aliasing

    Multisample anti-aliasing (MSAA) is a type of spatial anti-aliasing, a technique used in computer graphics to remove jaggies. It is an optimization of supersampling, where only the necessary parts are sampled more. Jaggies are only noticed in a small area, so the area is quickly found, and only that is anti-aliased.

  4. Fast approximate anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Fast_approximate_anti-aliasing

    The main advantage of this technique over conventional spatial anti-aliasing is that it does not require large amounts of computing power.It achieves this by smoothing undesirable jagged edges ("jaggies") [4] as pixels, according to how they appear on-screen, rather than analyzing the 3D model itself, as in conventional spatial anti-aliasing. [1]

  5. Deep Learning Super Sampling - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_super_sampling

    The first step is an image enhancement network which uses the current frame and motion vectors to perform edge enhancement, and spatial anti-aliasing. The second stage is an image upscaling step which uses the single raw, low-resolution frame to upscale the image to the desired output resolution.

  6. Direct2D - Wikipedia

    en.wikipedia.org/wiki/Direct2D

    The resulting performance is generally better than entirely CPU-based approaches and requires no ancillary storage for multisample or stencil state; Direct2D renders directly into an aliased framebuffer with properly antialiased results. Direct2D’s primary disadvantage is [that] the ultimate performance is determined not by the GPU (doing ...

  7. Deep Learning Anti-Aliasing - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_anti-aliasing

    Deep Learning Anti-Aliasing (DLAA) is a form of spatial anti-aliasing created by Nvidia. [1] DLAA depends on and requires Tensor Cores available in Nvidia RTX cards. [1]DLAA is similar to Deep Learning Super Sampling (DLSS) in its anti-aliasing method, [2] with one important differentiation being that the goal of DLSS is to increase performance at the cost of image quality, [3] whereas the ...

  8. Morphological antialiasing - Wikipedia

    en.wikipedia.org/wiki/Morphological_antialiasing

    Anti-aliasing is achieved by blending pixels in these borders, according to the pattern they belong to and their position within the pattern. [1] [2] [3] Enhanced subpixel morphological antialiasing, or SMAA, is an image-based GPU-based implementation of MLAA [4] developed by Universidad de Zaragoza and Crytek. [5]

  9. Temporal anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Temporal_anti-aliasing

    Temporal anti-aliasing (TAA) is a spatial anti-aliasing technique for computer-generated video that combines information from past frames and the current frame to remove jaggies in the current frame. In TAA, each pixel is sampled once per frame but in each frame the sample is at a different location within the frame.