https://github.com/Ha0Tang/SelectionGAN
공식 코드Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation
Papers with Code 아카이브
1 Image, 2*2 Stitching
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Hamsterrrrrrrrr/multiscale-ssh
공식 코드Multi-scale decomposition of sea surface height snapshots using machine learning
https://github.com/Harry-Thasarathan/TCVC
공식 코드https://github.com/HelenMao/MSGAN
공식 코드Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis
https://github.com/HelenMao/SAVI2I
공식 코드Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors
https://github.com/HideUnderBush/UI2I_via_StyleGAN2
공식 코드Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network
https://github.com/Hindawi91/Pseudo_Supervised_Metrics
공식 코드https://github.com/Honlan/DMT
공식 코드Disentangled Makeup Transfer with Generative Adversarial Network
https://github.com/HsinYingLee/DRIT
공식 코드Diverse Image-to-Image Translation via Disentangled Representations
https://github.com/IDKiro/MCT
공식 코드Multi-Curve Translator for High-Resolution Photorealistic Image Translation
https://github.com/IDKiro/sdxs
공식 코드SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions
https://github.com/IGLICT/DeepFaceDrawing-Jittor
공식 코드https://github.com/IVRL/ComicsDepth
공식 코드https://github.com/IshmaelBelghazi/ALI
공식 코드https://github.com/ItzikMalkiel/AGB
공식 코드Adaptive Gradient Balancing for UndersampledMRI Reconstruction and Image-to-Image Translation
https://github.com/IyatomiLab/LeafGAN
공식 코드LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis
https://github.com/JDAI-CV/FADA
공식 코드Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation
https://github.com/JOP-Lee/READ-Large-Scale-Neural-Scene-Rendering-for-Autonomous-Driving
공식 코드READ: Large-Scale Neural Scene Rendering for Autonomous Driving
https://github.com/JarrentWu1031/CCPL
공식 코드CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer
https://github.com/Jian-danai/Decompose-Distill-BeautyGAN
공식 코드Compressing Facial Makeup Transfer Networks by Collaborative Distillation and Kernel Decomposition
https://github.com/JianghaoWu/FPL-UDA
공식 코드https://github.com/JunlinHan/CWR
공식 코드https://github.com/JunlinHan/DCLGAN
공식 코드Dual Contrastive Learning for Unsupervised Image-to-Image Translation
https://github.com/KAIST-VICLab/C-DiffSET
공식 코드https://github.com/KU-CVLAB/InstaFormer
공식 코드InstaFormer: Instance-Aware Image-to-Image Translation with Transformer
https://github.com/KU-CVLAB/LANIT
공식 코드LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data
https://github.com/KaimingHe/resnet-1k-layers
공식 코드https://github.com/Kaiseem/AD-GAN
공식 코드AD-GAN: End-to-end Unsupervised Nuclei Segmentation with Aligned Disentangling Training
https://github.com/Kaminyou/Dense-Normalization
공식 코드https://github.com/KarlXing/LUSR
공식 코드Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation
https://github.com/LCAD-UFES/publications-arruda-ijcnn-2019
공식 코드Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night
https://github.com/LS4GAN/uvcgan4slats
공식 코드https://github.com/MICV-yonsei/CT2MRI
공식 코드Slice-Consistent 3D Volumetric Brain CT-to-MRI Translation with 2D Brownian Bridge Diffusion Model
https://github.com/MIDA-group/CoMIR
공식 코드CoMIR: Contrastive Multimodal Image Representation for Registration
https://github.com/MIDA-group/MultiRegEval
공식 코드Is Image-to-Image Translation the Panacea for Multimodal Image Registration? A Comparative Study
https://github.com/MInner/lrmf
공식 코드Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.