https://github.com/LeChangAlex/GAN-Metric
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Papers with Code 아카이브
Face Generation
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Face generation is the task of generating (or interpolating) new faces from an existing dataset.
The state-of-the-art results for this task are located in the Image Generation parent.
<span style="color:grey; opacity: 0.6">( Image credit: Progressive Growing of GANs for Improved Quality, Stability, and Variation )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Leminhbinh0209/AAAI22-ADD
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/Lotayou/everybody_dance_now_pytorch
https://github.com/MNaplesDevelopment/DCGAN-PyTorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/MNaplesDevelopment/Deep-Convolutional-Generative-Adversarial-Networks
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/MNaplesDevelopment/MNIST-DCGAN-PyTorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/MS-Mind/MS-Code-06/tree/main/PGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Mind23-2/MindCode-13
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/Mind23-2/MindCode-5/tree/main/PGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Mind23-2/MindCode-95
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/MindSpore-paper-code-2/code2/tree/main/PGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/MindSpore-scientific-2/code-10/tree/main/mgan-mindspore
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/MindSpore-scientific-2/code-4/tree/main/mgan-mindspore
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/MindSpore-scientific-2/code-7/tree/main/HCP_Avatar_Inferrence
GSmoothFace: Generalized Smooth Talking Face Generation via Fine Grained 3D Face Guidance
https://github.com/MindSpore-scientific/code-2/tree/main/Three-Dimensional-Lip-Motion-Network-for-Text-Independent-Speaker-Recognition-master
Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition
https://github.com/NickKaparinos/Google-Landmark-Recognition-2021
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/NikhitaMethwani/Deep-Fakes-Cars-Generation
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/NoahBarrett98/ProgressiveGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Novemser/deep-imitation
https://github.com/Olksndr/FaceShifter
FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping
https://github.com/OpenTalker/SadTalker
https://github.com/PacktPublishing/Hands-On-Image-Generation-with-TensorFlow-2.0/tree/master/Chapter07
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/PaddlePaddle/PLSC
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/PaddlePaddle/PaddleClas
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/Panagiotou/Procedural3DTerrain
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/Panagiotou/Random3DTerrain
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/PrasannaPulakurthi/ProGAN_PyTorch
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/PrashanthaTP/wav2mov
A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild
https://github.com/RAGHAV2998/Everybody-Can-Dance-Now-Video-game-version-
https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/Recognito-Vision/Face-SDK-Linux-Demos
Cross-Age Contrastive Learning for Age-Invariant Face Recognition
https://github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetection
DeepFakes: a New Threat to Face Recognition? Assessment and Detection
https://github.com/RocketFlash/easy_metric_learning/tree/master/tools
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
https://github.com/RyanWu2233/Style_GAN2_FFHQ
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/SHI-Labs/Neighborhood-Attention-Transformer
https://github.com/Sangohe/pgan_thesis
Progressive Growing of GANs for Improved Quality, Stability, and Variation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.