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/RuiLiFeng/noise
https://github.com/RyanWu2233/Style_GAN2_FFHQ
https://github.com/RyanWu2233/Style_GAN2_TWDNE
https://github.com/SJHNJU/Gated_PixelCNN
https://github.com/SJHNJU/gated-pixelcnn
https://github.com/Se-Hun/GAN_Study
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/SeniorDev009/ONNX-project
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/Sezoir/DCGAN-Dog-Generator
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/ShreyasArthur/StyleGAN-2-with-Urban-Plans
https://github.com/SiavashCS/sgan_simple
https://github.com/SimRunBot/DCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/SimoneDutto/EDSR
https://github.com/Soldie/DeOldify-colorir-imagens-antigas
https://github.com/Soumya1612-Rasha/Keras-GAN_rasha
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/SoumyadeepJana/CelebrityFaceGeneration
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/SpikeKing/stylegan2encoder-my
https://github.com/SzuPc/MindSpore-StyleGAN2
https://github.com/TUM-ML-Lab18/FaceSwap
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/TahmasbiM/Example
https://github.com/Takuya-Shuto-engineer/PokemonGAN
https://github.com/Tejas-Nanaware/GAN-Anime-Characters
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/TomokiKomiya/SRGAN-keras
https://github.com/UBC-Computer-Vision-Group/DwNet
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/UdbhavPrasad072300/GANs-Implementations
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/Uemuet/-gan
https://github.com/Uemuet/gan2
https://github.com/Uemuet/imet
https://github.com/Uemuet/imet2
https://github.com/Uemuet/stylegan2
https://github.com/Uemuet/stylegan22
https://github.com/VIRUS-ATTACK/DCGAN-GPU-IMPLEMENTATION
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/VIRUS-ATTACK/DCGAN-implementation.
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Vinayakam19/Deep-Convolution-Generative-Adversarial-Networks
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Vinayakam19/GAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Vishal-V/StackGAN
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.