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csslc/CCSR

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605 星标·43 分支·Python·Apache-2.0·4 次浏览

CCSR

Improving the Stability and Efficiency of Diffusion Models for Content Consistent Super-Resolution

Features

  • Super Resolution - Content-consistent super-resolution using stable diffusion.

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常见问题解答

csslc/ccsr 是做什么的?

Improving the Stability and Efficiency of Diffusion Models for Content Consistent Super-Resolution

csslc/ccsr 的主要功能有哪些?

csslc/ccsr 的主要功能包括:Super Resolution。

csslc/ccsr 有哪些开源替代品?

csslc/ccsr 的开源替代品包括: spipm/depixelization_poc — This project is an AI upscaling framework and deep learning image restorer designed to estimate original source pixels… paddlepaddle/paddlegan — PaddleGAN is a generative AI framework and deep learning computer vision library built on the PaddlePaddle framework.… arbez-zebra/sceesr. bichunyang419/deedsr. bowenchai/quantvsr. arctichare105/s3diff.

CCSR 的开源替代方案

相似的开源项目,按与 CCSR 的功能重合度排序。
  • spipm/depixelization_pocspipm 的头像

    spipm/Depixelization_poc

    4,535在 GitHub 上查看↗

    This project is an AI upscaling framework and deep learning image restorer designed to estimate original source pixels from low-resolution inputs. It functions as a super-resolution reconstruction system that transforms pixelated images into high-resolution versions by restoring high-frequency details and sharpening edges. The system utilizes a convolutional neural network pipeline to analyze pixel data and perform digital image restoration. It employs pixel-shuffle upsampling to rearrange channel dimensions into spatial dimensions, which increases resolution while reducing checkerboard artif

    Python
    在 GitHub 上查看↗4,535
  • paddlepaddle/paddleganPaddlePaddle 的头像

    PaddlePaddle/PaddleGAN

    8,043在 GitHub 上查看↗

    PaddleGAN is a generative AI framework and deep learning computer vision library built on the PaddlePaddle framework. It serves as a toolkit for image and video synthesis, providing a collection of generative adversarial network implementations for creating synthetic visual content. The library focuses on advanced synthesis capabilities, including the generation of talking heads through lip motion synchronization and the creation of synthetic videos via motion transfer from driving sequences. It provides tools for domain-to-domain translation, allowing for image style transfer and the transfo

    Pythonanimeganv2basicvsrpluspluscyclegan
    在 GitHub 上查看↗8,043
  • arbez-zebra/sceesrA

    ARBEZ-ZEBRA/SCEESR

    0在 GitHub 上查看↗
    在 GitHub 上查看↗0
  • arctichare105/s3diffA

    ArcticHare105/S3Diff

    0在 GitHub 上查看↗
    在 GitHub 上查看↗0
查看 CCSR 的所有 30 个替代方案→