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/lukedeo/keras-acgan
https://github.com/lukemelas/unsupervised-image-segmentation
https://github.com/lukovnikov/improved_wgan_training
https://github.com/lupalab/flowscan
https://github.com/luqui/big-sleep
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/lvyufeng/MindSpore-GAN
https://github.com/mahbouldom/StyleGAN2
https://github.com/mahmoudnafifi/HistoGAN
https://github.com/manicman1999/StyleGAN2-Tensorflow-2.0
https://github.com/markmaxt/VideoSR
https://github.com/marload/GANs-TensorFlow2
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/marload/TensorFlow2-GANs
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/matjazmav/fri-2021-ibb-seminar
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/matsagad/mres-project
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
https://github.com/mattya/chainer-DCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/mauriceweiler/MobiusCNNs
https://github.com/maxencealluin/mnist_DCGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/maxmax1992/WGAN_WGAN-GP
https://github.com/mbarbetti/tf-gen-models
https://github.com/mbbrodie/stylegan2
https://github.com/mcclow12/wgan-gp-pytorch
https://github.com/mchiappe83/Generate_Faces
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/mehdidc/hybrid-keras
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/mhuse/StyleGAN2LatentspaceInterpolation
https://github.com/michael13162/DoodleGAN
https://github.com/mickaelChen/GMV
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/mikelasz/fair-psp
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
https://github.com/mindspore-ai/models/tree/master/research/cv/dcgan
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/mingtaoguo/biggan-tensorflow
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/mingyuanzhou/sid-lsg
Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step
https://github.com/mingyuliutw/UNIT
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/minyoungg/GAN-Transform-and-Project
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/minyoungg/pix2latent
Large Scale GAN Training for High Fidelity Natural Image Synthesis
https://github.com/mitscha/dplc
https://github.com/ml-research/i2p
A Novel Sampling Scheme for Text- and Image-Conditional Image Synthesis in Quantized Latent Spaces
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.