https://github.com/AlliBalliBaba/PixFace-Neural-Network
Image-to-Image Translation with Conditional Adversarial Networks
Papers with Code 아카이브
Image Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 23
- 평가표
- 93
- 보존된 평가 기록
- 870
Image Generation (synthesis) is the task of generating new images from an existing dataset.
- Unconditional generation refers to generating samples unconditionally from the dataset, i.e. $p(y)$
- Conditional image generation (subtask) refers to generating samples conditionally from the dataset, based on a label, i.e. $p(y|x)$.
In this section, you can find state-of-the-art leaderboards for unconditional generation. For conditional generation, and other types of image generations, refer to the subtasks.
<span style="color:grey; opacity: 0.6">( Image credit: StyleGAN )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/AlphaKong/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Aminsaffar/DE-GAN
Generative Adversarial Networks with Decoder-Encoder Output Noise
https://github.com/Amrou7/Sin-GAN-master
SinGAN: Learning a Generative Model from a Single Natural Image
https://github.com/AnatoliiPotapov/inpainting_FRRN
Progressive Image Inpainting with Full-Resolution Residual Network
https://github.com/Anderies/stochastic-constant-pruninglayers
https://github.com/AndreasWieg/PC-PGGAN
https://github.com/AndreiMoraru123/ContextCollector
https://github.com/AndreiMoraru123/Watch-and-Tell
https://github.com/AndreyBesedin/ImageClassification
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Andribi/A2MF_AP
https://github.com/AndyDodss/iicnn
Generating Images with Perceptual Similarity Metrics based on Deep Networks
https://github.com/AngusG/bn-advex-zhang-fixup
https://github.com/AniSundar18/AlignedForensics
On the Effectiveness of Dataset Alignment for Fake Image Detection
https://github.com/Aniket7/VGGNet-CNN-architecture
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/AnishWalawalkar/cs231
Image Inpainting for Irregular Holes Using Partial Convolutions
https://github.com/Ankur3107/awesome-daily-blog
TextKD-GAN: Text Generation using KnowledgeDistillation and Generative Adversarial Networks
https://github.com/AntixK/PyTorch-VAE
Generating Images with Perceptual Similarity Metrics based on Deep Networks
https://github.com/AntixK/mean_spectral_norm
Mean Spectral Normalization of Deep Neural Networks for Embedded Automation
https://github.com/AntonioAlgaida/Edge.SRGAN
https://github.com/Anuranjan-Kumar/kaggle_cats-vs-dogs
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Anyesh/skeatch-to-anime
https://github.com/ApolloScapeAuto/dataset-api
https://github.com/AquibPy/Cycle-GAN
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/AquibPy/Pix2Pix-Conditional-GANs
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/ArMaxik/Progressive_growing_of_GANs-Pytorch_implementation
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Archangel212/psgan-batik
https://github.com/Archangel212/psgan-pytorch
https://github.com/ArenGolazizian/Pix2Pix-Cityscapes-Seg2Real
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/ArifRaihan/Deeper-CNN-Architectures-for-Image-Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ArkaJU/Image-Colorization-CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Arktis2022/mini-vq-discrete-absorbing-diffusion
https://github.com/Armxyz1/Results-on-RFW
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/Ars235/Novelty_Detection
https://github.com/Aruie/Aru_StyleGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Aryan05/Generative-Modelling-of-Images-from-Speech_Speech2Face
Wav2Pix: Speech-conditioned Face Generation using Generative Adversarial Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.