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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zichongc/doesfs
공식 코드Deformable One-shot Face Stylization via DINO Semantic Guidance
https://github.com/zipengxuc/spectralclip
공식 코드SpectralCLIP: Preventing Artifacts in Text-Guided Style Transfer from a Spectral Perspective
https://github.com/zipengxuc/stylerdalle
공식 코드https://github.com/ziyuey/cssstn
공식 코드https://github.com/ziyuzhao-zzy/logostylefool
공식 코드LogoStyleFool: Vitiating Video Recognition Systems via Logo Style Transfer
https://github.com/zkawfanx/atlantis
공식 코드Atlantis: Enabling Underwater Depth Estimation with Stable Diffusion
https://github.com/zkx06111/rediffusion
공식 코드ReDi: Efficient Learning-Free Diffusion Inference via Trajectory Retrieval
https://github.com/zlh-thu/StealingVerification
공식 코드Defending against Model Stealing via Verifying Embedded External Features
https://github.com/zmd971202/IronyGeneration
공식 코드https://github.com/zxhuang97/Official-implementation-StyleMixer
공식 코드https://github.com/zyainfal/One-Shot-Face-Swapping-on-Megapixels
공식 코드https://github.com/zyxelsa/InST
공식 코드https://github.com/zyxelsa/cast_pytorch
공식 코드Domain Enhanced Arbitrary Image Style Transfer via Contrastive Learning
https://gitlab.com/deepet/faket
공식 코드FakET: Simulating Cryo-Electron Tomograms with Neural Style Transfer
https://gitlab.com/paloha/redistributor
공식 코드https://gitlab.lrz.de/hctl/Iris-Obfuscation-Benchmark
공식 코드Trade-offs in Privacy-Preserving Eye Tracking through Iris Obfuscation: A Benchmarking Study
https://gitlab.lrz.de/hctl/Iris-Style-Transfer
공식 코드https://huggingface.co/datasets/jdustinwind/Polite
공식 코드Pay Attention to Your Tone: Introducing a New Dataset for Polite Language Rewrite
https://huggingface.co/nevmenandr/char-based-lstm-russian-poetry-pasternak
공식 코드Identifying the style by a qualified reader on a short fragment of generated poetry
https://worksheets.codalab.org/worksheets/0xe3eb416773ed4883bb737662b31b4948
공식 코드Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer
https://github.com/101vinayak/Neural-Style-Transfer
https://github.com/11aditya11/Neural_Style_Transfer
https://github.com/2023-MindSpore-1/ms-code-134
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-158
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/ArbitraryStyleTransfer
https://github.com/2023-MindSpore-1/ms-code-184
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/StyTr-2
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/StyTr-2
https://github.com/2023-MindSpore-4/Code11/tree/main/SinGAN
SinGAN-Seg: Synthetic training data generation for medical image segmentation
https://github.com/2023-MindSpore-4/Code12/tree/main/liliang/ssa
Unsupervised Coherent Video Cartoonization with Perceptual Motion Consistency
https://github.com/2023-MindSpore-4/Code14/tree/main/SinGAN
SinGAN-Seg: Synthetic training data generation for medical image segmentation
https://github.com/2023-MindSpore-4/Code8/tree/main/ArbitraryStyleTransfer
Exploring the structure of a real-time, arbitrary neural artistic stylization network
https://github.com/2024-MindSpore-1/Code10/tree/main/DRAN
DRAN: Detailed Region-Adaptive Normalization for Conditional Image Synthesis
https://github.com/7-B/yoco
https://github.com/780753368/Deep-Feature-Perturbation
Diversified Arbitrary Style Transfer via Deep Feature Perturbation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.