https://github.com/IShengFang/ishengfang
Self-Contained Stylization via Steganography for Reverse and Serial Style Transfer
Papers with Code 아카이브
Drawing Pictures
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Iamnotabear/Neural-Style-Transfer
https://github.com/IdanAzuri/pytorch_fewshot_with_deep_photo
https://github.com/Ign0reLee/EMD_Neural_Style_Transfer_with_Tensorflow
A Unified Framework for Generalizable Style Transfer: Style and Content Separation
https://github.com/IndigoAI/FontGenerator
https://github.com/Intelligent-Imaging-Center/Spectral-Reconstruction
https://github.com/IpastorSan/neural_style_transfer
https://github.com/J3698/AdaIN-reimplementation
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
https://github.com/JL321/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/JamesLiao714/MC_GAN
https://github.com/JaryV/CycleGAN_OldYoung
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/JasperNg/ColorPreservationYUV
https://github.com/Jay0505/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/JennEYoon/Coursera-DLAI
https://github.com/Jeongseungwoo/Singing-Style-transfer
Singing Style Transfer Using Cycle-Consistent Boundary Equilibrium Generative Adversarial Networks
https://github.com/JeongsolKim/BiS400_term_project
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
https://github.com/JimmyDoan1309/Neural-Style-Transfer
https://github.com/Jitensid/Neural-Style-Transfer
https://github.com/JohanYe/CycleGAN-Pokemon
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/JohanZYe/CycleGAN-Pokemon
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/JorgeGtz/TextureNets_implementation
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
https://github.com/Josien94/MLiP
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/JustWon/mystyletransfer
https://github.com/Justin-Tan/generative-compression
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Jwrede/neural_style_transfer
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
https://github.com/KaiyangZhou/ssdg-benchmark
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
https://github.com/Kalyan0821/NST
https://github.com/Kalyan0821/myelinfoundry-challenge
https://github.com/KamilCendrowicz/NST
https://github.com/KamitaniLab/icnn
https://github.com/KangDo96/Github-Ranking
https://github.com/Karan-kapadia/Style-Transfer-karan
https://github.com/KathyReid/opensource-voice-tools
Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis
https://github.com/Kautenja/a-neural-algorithm-of-artistic-style
https://github.com/KingJamesSong/DifferentiableSVD
https://github.com/KinglittleQ/GST-Tacotron
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.