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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/kakaoenterprise/kakaoenterprise.github.io
A Plug-in Method for Representation Factorization in Connectionist Models
https://github.com/kaletap/language-style-transfer-pytorch
https://github.com/kaletap/nlp-experiments
A Probabilistic Formulation of Unsupervised Text Style Transfer
https://github.com/kaletap/nlp-style-transfer
https://github.com/kaminyou/urust
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/kanishk16/Image-Style-Transfer
https://github.com/karl-hajjar/Generative-Adversarial-Networks
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/karuj/StyleTransfer
https://github.com/keonlee9420/Comprehensive-Tacotron2
https://github.com/keonlee9420/Cross-Speaker-Emotion-Transfer
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
https://github.com/khornlund/CycleGAN-Music-Style-Transfer-1
https://github.com/khush3/GAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/kidach1/NeuralArtisticStyle
https://github.com/kirill-ionkin/NST_Gatys
https://github.com/knurpsbram/autovc_wavenetvocoder_griffinlim_experiments
AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
https://github.com/kramer99/neural-style-transfer
https://github.com/ksivaman/super-res
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/ku2482/vae.pytorch
https://github.com/kumnikhil/christmAIs_replica
https://github.com/kvsnoufal/neural_style_transfer
https://github.com/kynk94/TF2-Image-Generation
https://github.com/kyuer/language-style-transfer
https://github.com/kzkymur/transition
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/labmlai/annotated_deep_learning_paper_implementations
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/laughtervv/tf_neural_renderer
https://github.com/lcosmo/LIMP
LIMP: Learning Latent Shape Representations with Metric Preservation Priors
https://github.com/lcosmo/isospectralization
Isospectralization, or how to hear shape, style, and correspondence
https://github.com/leehomyc/cyclegan-1
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/lengstrom/fast-style-transfer
https://github.com/leolle/StyleTransfer
https://github.com/leonardoperu/Monetmaker
https://github.com/leongatys/PytorchNeuralStyleTransfer
https://github.com/lhannest/neuralstyle
https://github.com/liamheng/pytorch1.4-wct
https://github.com/libreai/neural-painters-x
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.