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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mindspore-lab/mindediting
공식 코드Tunable Convolutions with Parametric Multi-Loss Optimization
https://github.com/mingyuliutw/CoGAN
공식 코드https://github.com/mingyuliutw/UNIT
공식 코드https://github.com/mirthai/fast-ddpm
공식 코드Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation
https://github.com/misaliet/seamless-satellite-image-synthesis
공식 코드https://github.com/mit-acl/dc2g
공식 코드https://github.com/mlandcv/Auxilliary_Reconstruction_GAN
공식 코드Unsupervised Image Translation using Adversarial Networks for Improved Plant Disease Recognition
https://github.com/mlvlab/scdm
공식 코드Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis
https://github.com/mobaidoctor/med-ddpm
공식 코드Conditional Diffusion Models for Semantic 3D Brain MRI Synthesis
https://github.com/mohammadrsalmanpour/allmetrics-a-unified-python-library-for-standardized-metric-evaluation-in-machine-learning
공식 코드https://github.com/mpatacchiola/Y-AE
공식 코드Y-Autoencoders: disentangling latent representations via sequential-encoding
https://github.com/msseibel/accut
공식 코드https://github.com/mu-cai/frequency-domain-image-translation
공식 코드Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving
https://github.com/nadeemlab/CEP
공식 코드Visualizing Missing Surfaces In Colonoscopy Videos using Shared Latent Space Representations
https://github.com/nehamjain10/trudgcr
공식 코드Towards Realistic Underwater Dataset Generation and Color Restoration
https://github.com/nicecv/diffharmony
공식 코드DiffHarmony: Latent Diffusion Model Meets Image Harmonization
https://github.com/nithin-gk/at-ddpm
공식 코드https://github.com/nk-cs-zzl/ian
공식 코드Designing An Illumination-Aware Network for Deep Image Relighting
https://github.com/noureddinekhiati/semi-supervised-lung-segmentation
공식 코드https://github.com/nvlabs/MUNIT
공식 코드https://github.com/nvlabs/imaginaire
공식 코드COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder
https://github.com/ondyari/FaceForensics
공식 코드FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/onuriel/PermutedAdaIN
공식 코드Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image Classification
https://github.com/ood2iid/code
공식 코드Rethinking Machine Learning Robustness via its Link with the Out-of-Distribution Problem
https://github.com/orpatashnik/BalaGAN
공식 코드BalaGAN: Image Translation Between Imbalanced Domains via Cross-Modal Transfer
https://github.com/patrickrperrine/comp-choreo
공식 코드KP-RNN: A Deep Learning Pipeline for Human Motion Prediction and Synthesis of Performance Art
https://github.com/petrmokrov/energy-guided-entropic-ot
공식 코드https://github.com/pfriedri/cwdm
공식 코드cWDM: Conditional Wavelet Diffusion Models for Cross-Modality 3D Medical Image Synthesis
https://github.com/phoenix104104/fast_blind_video_consistency
공식 코드https://github.com/pix2pixzero/pix2pix-zero
공식 코드https://github.com/polimi-ispl/icpr-benford-gan
공식 코드https://github.com/polimi-ispl/icpr2020dfdc
공식 코드https://github.com/project-monai/generativemodels
공식 코드Generative AI for Medical Imaging: extending the MONAI Framework
https://github.com/pshams55/GAN-Case-Study
공식 코드Image Synthesis with Adversarial Networks: a Comprehensive Survey and Case Studies
https://github.com/puckikk1202/difffacesketch2023
공식 코드DiffFaceSketch: High-Fidelity Face Image Synthesis with Sketch-Guided Latent Diffusion Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.