https://github.com/jiajunhua/tkarras-progressive_growing_of_gans
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Papers with Code 아카이브
Image Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/jiamings/a-nice-mc
https://github.com/jiamings/d2c
D2C: Diffusion-Denoising Models for Few-shot Conditional Generation
https://github.com/jiamings/d2c_pre_release
D2C: Diffusion-Denoising Models for Few-shot Conditional Generation
https://github.com/jiangshuyi0v0/cvd-gan
https://github.com/jiangsikai/Person_reID_baseline_pytorch
Joint Discriminative and Generative Learning for Person Re-identification
https://github.com/jianzhangcs/GSR
https://github.com/jiashunwang/ZPT
https://github.com/jiazhi412/strong_attribute_bias
A Style-Based Generator Architecture for Generative Adversarial Networks
https://github.com/jie-1203/adwm
SSDiff: Spatial-spectral Integrated Diffusion Model for Remote Sensing Pansharpening
https://github.com/jie-1203/wfanet
SSDiff: Spatial-spectral Integrated Diffusion Model for Remote Sensing Pansharpening
https://github.com/jielin-qiu/mm_robustness
Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift
https://github.com/jihoonerd/Unsupervised-Representation-Learning-with-Deep-Convolutional-Generative-Adversarial-Networks
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/jimheaton/Ultra96_ML_Embedded_Workshop
https://github.com/jimzers/stylegan2-colabs
A Style-Based Generator Architecture for Generative Adversarial Networks
https://github.com/jinhaoduan/SecMI-LDM
Are Diffusion Models Vulnerable to Membership Inference Attacks?
https://github.com/jinlong17/da-detect
Domain Adaptive Faster R-CNN for Object Detection in the Wild
https://github.com/jinsel/Text-to-Image-Generation
https://github.com/jinyangyuan/genesis
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
https://github.com/jis478/AniGAN
AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation
https://github.com/jishubasak/Punny-Caption--Exploring-Image-Captioning
https://github.com/jiupinjia/stylized-neural-painting
https://github.com/jiweibo/imagenet
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/jixinya/EVP
https://github.com/jizongFox/ReproduceAdaptSegNet
Learning to Adapt Structured Output Space for Semantic Segmentation
https://github.com/jjunak-yun/FLowHigh_code
https://github.com/jleinonen/keras-fid
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
https://github.com/jlindsey15/DRAM
https://github.com/jm199504/VGG-NET
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/jmyoon1/adp
Improved Techniques for Training Score-Based Generative Models
https://github.com/joanfmendo/MixNMatch
MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation
https://github.com/joanrod/figure-diffusion
High-Resolution Image Synthesis with Latent Diffusion Models
https://github.com/joaocneves/gan_fingerprint_removal
GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detection
https://github.com/joey00072/DCGAN-Genrating-anime-faces
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/joeylitalien/celeba-gan-pytorch
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/joeynavarro/facial_expression_classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.