Papers with Code 아카이브
Conditional Image Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 11
- 보존된 평가 기록
- 75
Conditional image generation is the task of generating new images from a dataset conditional on their class.
<span style="color:grey; opacity: 0.6">( Image credit: PixelCNN++ )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/polmonroig/faceGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/porimol/GAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/pranavbudhwant/ACVAEGAN
https://github.com/prodillo/GAN_project
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/ps-dban/Gradient-Workflows-Tutorial
https://github.com/pskrunner14/face-DCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/psmenon/DCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/qinpengzhi/myDCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/qnduan/wgan-scrna
https://github.com/raahii/evan
https://github.com/raahii/video-gans-evaluation
https://github.com/rahulkulhalli/ISIC2019
https://github.com/rahuls02/Image-Noise-Reduction
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
https://github.com/rajprakrit/DCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/rajveen/ChangeMyPet
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/rampage644/wavenet
https://github.com/ravasconcelos/flowers_dcgan
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/raylyh/misgan-reimplementation
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/recluse27/Colorizator
https://github.com/richardrl/gan-pytorch
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/ricky40403/BlurPool
https://github.com/rickyHong/pix2pixHD-repl
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/rkem1542/EDSR-pytorch
https://github.com/rkorzeniowski/bigbigan-pytorch
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/robbiebarrat/art-DCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/robertluxemburg/stylegan2encoder
https://github.com/roberttwomey/machine-imagination-workshop
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/rohitkuk/AnimeGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/rolux/stylegan2encoder
https://github.com/rolux/stylegan2tpu
https://github.com/rosasalberto/StyleGAN2-TensorFlow-2.x
https://github.com/rosinality/sagan-pytorch
https://github.com/rosinality/stylegan2-pytorch
https://github.com/royg27/BIGRoC
https://github.com/ruiliu-ai/DivCo
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.