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/rwightman/pytorch-image-models
https://github.com/sagy101/SoundGAN
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/sahand68/Deep-Convolutional-GAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/sahidrahmanxx12/TEMPEK
https://github.com/sahil02235/DCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/sanghviyashiitb/GANS-VanillaAndMinibatchDiscrimination
https://github.com/sanghyun-son/EDSR-PyTorch
https://github.com/sangyun884/Face2Webtoon
https://github.com/sangyun884/fast-ode
https://github.com/santoshchaurasiyacs/StyleGANv2
https://github.com/sarus-tech/tf2-published-models
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/sarus-tech/tf2-published-models/tree/master/gated_pixelcnn
https://github.com/sbarratt/inception-score-pytorch
https://github.com/sdoria/SimpleSelfAttention
https://github.com/seanmullery/iWGAN
https://github.com/seungjunlee96/AnoGAN-pytorch
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/sh4174/3d-stylegan2-ada
https://github.com/shahbuland/basic-gans
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/shalabh147/DCGan
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/shalabh147/DCGan-Keras
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/shaoanlu/faceswap-GAN
https://github.com/shaochenze/ear
https://github.com/shepnerd/AttenNorm
https://github.com/sherdencooper/dcgan-mnist
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/shilin-lu/vine
TF-ICON: Diffusion-Based Training-Free Cross-Domain Image Composition
https://github.com/shivamswarnkar/Image-Generator
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/shpda/text-to-image-gen-model-acgan
https://github.com/shuliyao/GANimation_TL
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/shvmshri/DCGAN_Tensorflow
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/shyam671/Twin_Auxiliary_Classifier_GAN
https://github.com/sid0312/DC_GAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/sidward14/gan-lab
https://github.com/simon0987/ACGAN-implemented-with-pytorch
https://github.com/simplerick/stylegan2_pytorch
https://github.com/sirius-image-inpainting/Free-Form-Image-Inpainting-With-Gated-Convolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.