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2. Deep learning super sampling - Wikipedia

   en.wikipedia.org/wiki/Deep_learning_super_sampling

   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. Using just a single frame for upscaling means the neural network itself must generate a large amount of new information to produce the high resolution output, this can result in slight hallucinations ...

3. Text-to-image model - Wikipedia

   en.wikipedia.org/wiki/Text-to-image_model

   An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.

4. waifu2x - Wikipedia

   en.wikipedia.org/wiki/Waifu2x

   waifu2x is an image scaling and noise reduction program for anime-style art and other types of photos. [1] waifu2x was inspired by Super-Resolution Convolutional Neural Network (SRCNN). [2] [3] It uses Nvidia CUDA for computing, [4] although alternative implementations that allow for OpenCL [5] and Vulkan [6] have been created.

5. AI Image Generators Will Blow Your Mind. Here Are the 3 Best ...

   www.aol.com/lifestyle/ai-image-generators-blow...

   My comparison analyzed cost, ease of use, image resolution, dynamic range, composition, creativity, post-processing, and even speed. Along with those factors I also fed each with identical prompts ...

6. DALL-E - Wikipedia

   en.wikipedia.org/wiki/DALL-E

   Given an existing image, DALL-E 2 can produce "variations" of the image as individual outputs based on the original, as well as edit the image to modify or expand upon it. DALL-E 2's "inpainting" and "outpainting" use context from an image to fill in missing areas using a medium consistent with the original, following a given prompt.

7. Ideogram (text-to-image model) - Wikipedia

   en.wikipedia.org/wiki/Ideogram_(text-to-image_model)

   Ideogram was founded in 2022 by Mohammad Norouzi, William Chan, Chitwan Saharia, and Jonathan Ho to develop a better text-to-image model. [3]It was first released with its 0.1 model on August 22, 2023, [4] after receiving $16.5 million in seed funding, which itself was led by Andreessen Horowitz and Index Ventures.