Papers with Code 아카이브
Image Generation
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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/Electronicshelf/Quality-Guided-Sketch-to-Photo-Image-Synthesis
https://github.com/ElliottKasoar/GeneVAE
https://github.com/ElliottKasoar/gene-dag-vae
https://github.com/Elman295/Maximum-Classifier-Discrepancy-for-Unsupervised-Domain-Adaptation
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
https://github.com/Elman295/Unsupervised-Domain-Adaptation-by-Backpropagation-
https://github.com/Eltomad/insightface
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/EmilienDupont/wgan-gp
https://github.com/Emir-Liu/Cycle-GAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/EmptySamurai/pytorch-reconet
https://github.com/End2End-Diffusion/REPA-E
REPA-E: Unlocking VAE for End-to-End Tuning of Latent Diffusion Transformers
https://github.com/EngineeringSapien/NarutoCV
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EricAlcaide/MiniFold
https://github.com/Error-code404/Random-Unreal-Face
https://github.com/EstherBear/implementation-of-pruning-filters
https://github.com/EugenHotaj/pytorch-generative/blob/master/pytorch_generative/models/autoregressive/gated_pixel_cnn.py
https://github.com/EugenHotaj/pytorch-generative/blob/master/pytorch_generative/models/autoregressive/made.py
https://github.com/EugenHotaj/pytorch-generative/blob/master/pytorch_generative/models/autoregressive/nade.py
https://github.com/EugenHotaj/pytorch-generative/blob/master/pytorch_generative/models/autoregressive/pixel_cnn.py
https://github.com/EugenHotaj/pytorch-generative/blob/master/pytorch_generative/models/autoregressive/pixel_snail.py
https://github.com/EugenHotaj/pytorch-generative/blob/master/pytorch_generative/models/flow/nice.py
https://github.com/EugenHotaj/pytorch-generative/blob/master/pytorch_generative/models/vae/vd_vae.py
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images
https://github.com/EugenHotaj/pytorch-generative/blob/master/pytorch_generative/models/vae/vq_vae_2.py
https://github.com/EvZissel/LoBCoD
A Local Block Coordinate Descent Algorithm for the Convolutional Sparse Coding Model
https://github.com/Evavanrooijen/InfoGAN-PyTorch
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
https://github.com/EverLookNeverSee/diag2model
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EvgenyVendrov/DeepLearningCourse
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Evolving-AI-Lab/ppgn
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space
https://github.com/Evolving-AI-Lab/synthesizing
Generating Images with Perceptual Similarity Metrics based on Deep Networks
https://github.com/Eyyub/tensorflow-cyclegan
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/FHomps/ADViSE
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/FIT4003StackGAN/FIT4003-StackGAN-v2-Metamorphic-Testing
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
https://github.com/Fabienne703/Data
https://github.com/FaceOnLive/DeepFake-Detection-SDK-Linux
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/Faceplugin-ltd/FaceLivenessDetection-Android
https://github.com/Faceplugin-ltd/FaceRecognition-Android
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.