ESRGAN is described as '(Description from https://www.resetera.com/threads/ai-neural-networks-being-used-to-generate-hq-textures-for-older-games-you-can-do-it-yourself.88272/)' and is a Image Upscaling app in the photos & graphics category. There are more than 25 alternatives to ESRGAN, not only websites but also apps for a variety of platforms, including Windows, Linux, Mac and Flathub apps. The best ESRGAN alternative is Upscayl, which is both free and Open Source. Other great sites and apps similar to ESRGAN are REAL Video Enhancer, waifu2x, chaiNNer and Magnific AI.
Open source desktop tool using advanced AI to enlarge and enhance images without loss of quality, available for Linux, macOS, and Windows. Linux-first development gives early access to Linux users. Requires Vulkan compatible GPU for upscaling.
Cross-platform tool offering advanced video upscaling and frame interpolation using RIFE, RealESRGAN, Waifu2x, and IFRNET, with scene change detection, instant preview, Discord integration, and ability to enhance local files or YouTube videos on major operating systems.
Image Super-Resolution [upscaling] for Anime-style [low detail] art or images using Deep Convolutional Neural Networks.
A flowchart/node-based image processing GUI aimed at making chaining image processing tasks (especially upscaling done by neural networks) easy, intuitive, and customizable.
The most advanced AI upscaler & enhancer. Magnific can hallucinate and reimagine as many details as you wish guided by your own prompt and parameters!.
RealScaler is a Windows app based on Real-ESRGAN AI to enhance, enlarge and reduce noise in photographs and videos.
An Android application for super-resolution & interpolation. Contains RealSR-NCNN, SRMD-NCNN, RealCUGAN-NCNN, Real-ESRGAN-NCNN, Waifu2x-NCNN, Anime4kcpp, nearest, bilinear, bicubic, AVIR...
Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming language.
jdPixelUpscaler upscales images by simply replacing one pixel with several of the same color. For example, if you set the scaling factor to 2, one pixel becomes 2x2 pixels of the same color. No attention is paid to the surrounding pixels or to transitions.
Recent state-of-the-art super-resolution methods have achieved impressive performance on ideal datasets regardless of blur and noise. However, these methods always fail in real-world image super-resolution, since most of them adopt simple bicubic downsampling from high-quality...
Elevate your images with cutting-edge AI technology and a suite of tools for restoration, upscaling, and more.
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