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clovaai/stargan-v2

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3,610 星标·674 分支·Python·5 次浏览

Stargan V2

StarGAN v2 - Official PyTorch Implementation (CVPR 2020)

Features

  • Computer Vision Libraries - Official PyTorch implementation of StarGAN v2.
  • Domain Transfer and Translation - Diverse image synthesis across multiple domains.
  • Image Translation - Diverse image synthesis across multiple domains.

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Stargan V2 的开源替代方案

相似的开源项目,按与 Stargan V2 的功能重合度排序。
  • phillipi/pix2pixphillipi 的头像

    phillipi/pix2pix

    10,644在 GitHub 上查看↗

    pix2pix is a framework for image-to-image translation using conditional generative adversarial networks. It functions as a supervised trainer and visual domain mapper designed to learn a mapping between input and output images for style and domain transfer. The system utilizes a U-Net encoder-decoder architecture combined with a PatchGAN local discriminator to enforce high-frequency local consistency. It employs L1 loss regularization to ensure generated outputs remain structurally close to the ground truth. The project covers a broad range of computer vision capabilities, including semantic

    Lua
    在 GitHub 上查看↗10,644
  • junyanz/cycleganjunyanz 的头像

    junyanz/CycleGAN

    12,861在 GitHub 上查看↗

    CycleGAN is a generative adversarial network framework designed for unpaired image-to-image translation. It enables the conversion of images between two distinct visual domains using datasets that do not require direct one-to-one matching examples. The project implements a deep learning style transfer tool capable of artistic style transfer, object transfiguration, and domain-to-domain conversion. It uses a dual-generator architecture and cycle-consistency loss to ensure that images translated to a target domain and back recover their original state. The framework covers core machine learnin

    Lua
    在 GitHub 上查看↗12,861
  • nvidia/pix2pixhdNVIDIA 的头像

    NVIDIA/pix2pixHD

    6,920在 GitHub 上查看↗

    pix2pixHD is a conditional generative adversarial network designed to transform semantic label maps into high-resolution photorealistic images. It functions as a high-resolution image synthesizer and an image-to-image translation model capable of producing synthetic images at 2048x1024 resolution. The system includes a semantic image editor that allows for the modification of high-resolution visuals by updating the underlying semantic label maps. This enables interactive image editing and the generation of photorealistic images based on source images or discrete label maps. The framework pro

    Python
    在 GitHub 上查看↗6,920
  • carpedm20/discogan-pytorchcarpedm20 的头像

    carpedm20/DiscoGAN-pytorch

    1,097在 GitHub 上查看↗

    PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

    Jupyter Notebook
    在 GitHub 上查看↗1,097
查看 Stargan V2 的所有 30 个替代方案→

常见问题解答

clovaai/stargan-v2 是做什么的?

StarGAN v2 - Official PyTorch Implementation (CVPR 2020)

clovaai/stargan-v2 的主要功能有哪些?

clovaai/stargan-v2 的主要功能包括:Computer Vision Libraries, Domain Transfer and Translation, Image Translation。

clovaai/stargan-v2 有哪些开源替代品?

clovaai/stargan-v2 的开源替代品包括: junyanz/cyclegan — CycleGAN is a generative adversarial network framework designed for unpaired image-to-image translation. It enables… phillipi/pix2pix — pix2pix is a framework for image-to-image translation using conditional generative adversarial networks. It functions… nvlabs/munit — Multimodal Unsupervised Image-to-Image Translation. carpedm20/discogan-pytorch — PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks". nvidia/vid2vid — Pytorch implementation for high-resolution (e.g., 2048x1024) photorealistic video-to-video translation. It can be used… nvidia/pix2pixhd — pix2pixHD is a conditional generative adversarial network designed to transform semantic label maps into…