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/MinkaiXu/SobolevWassersteinGAN
https://github.com/Mmhmmmmm/ylg_pytorch
https://github.com/Mmhmmmmm/ylg_pytorvh
https://github.com/Mohanned-Elkholy/BigGan-model-inversion-with-image-transformations
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/Mohanned-Elkholy/ResNet-GAN
https://github.com/Murali81/InfoGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/MustafaMustafa/cosmoGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/MustafaMustafa/dcgan-tf-benchmark
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/NMADALI97/Learning-With-Wasserstein-Loss
https://github.com/NVlabs/stylegan2-ada-pytorch
https://github.com/NadimKawwa/DCGAN_faces
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/NariMo91/GANs-generative-art
https://github.com/Natsu6767/DCGAN-PyTorch
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/NawafAlsuwailem/artathon_code
https://github.com/Negus25/Mindspore-wgan_gp
https://github.com/Neptune-Trojans/GANs
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Newmu/dcgan_code
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/NicicDamjan/SoftKompjuting
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/NicolaBernini/PaperAnalysis_ICLR2021_NegativeDataAugmentation
https://github.com/Nirav-Agarwal/GANs
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Noxxel/floter
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/PDEUXA/AIF_CYCLEGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/PacktPublishing/Hands-On-Image-Generation-with-TensorFlow-2.0/tree/master/Chapter08
https://github.com/PaddlePaddle/PaddleMIX
https://github.com/Paul-Trax/GANs
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Prinsphield/GeneGAN
GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data
https://github.com/ProSTIGTeam/DCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/PsorTheDoctor/microarray-data
https://github.com/QuickSolverKyle/Tensorflow-MyGANs
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Rajjeshwar/DCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Ram81/AC-VAEGAN-PyTorch
https://github.com/Ranchofromxgd/DCGAN_mnist
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection
https://github.com/RikoLi/gan-acgface
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/RuiLiFeng/LAE
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.