https://github.com/rizavelioglu/tryoffdiff
공식 코드TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Models
Papers with Code 아카이브
Image-to-Image Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 11
- 평가표
- 38
- 보존된 평가 기록
- 195
Image-to-Image Translation is a task in computer vision and machine learning where the goal is to learn a mapping between an input image and an output image, such that the output image can be used to perform a specific task, such as style transfer, data augmentation, or image restoration.
<span style="color:grey; opacity: 0.6">( Image credit: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/rmokady/structural-analogy
공식 코드https://github.com/robert-graf/readable-conditional-denoising-diffusion
공식 코드Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation
https://github.com/royee182/dpl
공식 코드Dual Path Learning for Domain Adaptation of Semantic Segmentation
https://github.com/royorel/FFHQ-Aging-Dataset
공식 코드https://github.com/royorel/Lifespan_Age_Transformation_Synthesis
공식 코드https://github.com/rsummers11/CADLab
공식 코드https://github.com/sagiebenaim/DistanceGAN
공식 코드https://github.com/sagiebenaim/OneShotTranslation
공식 코드https://github.com/sagiebenaim/gan_bound
공식 코드Estimating the Success of Unsupervised Image to Image Translation
https://github.com/saic-mdal/HiDT
공식 코드https://github.com/samarthshukla/dcn
공식 코드Zero-Pair Image to Image Translation using Domain Conditional Normalization
https://github.com/samgregoost/Rethinking-CGANs
공식 코드Rethinking conditional GAN training: An approach using geometrically structured latent manifolds
https://github.com/sangwoomo/instagan
공식 코드https://github.com/sanofi-public/miphei-vit
공식 코드MIPHEI-ViT: Multiplex Immunofluorescence Prediction from H&E Images using ViT Foundation Models
https://github.com/sanoscience/simuscope
공식 코드https://github.com/sapphire497/style-transformer
공식 코드https://github.com/sarmadfismael/lrm_i2i
공식 코드https://github.com/seanjia/srunit
공식 코드Semantically Robust Unpaired Image Translation for Data with Unmatched Semantics Statistics
https://github.com/seasonSH/WarpGAN
공식 코드https://github.com/segmind/distill-sd
공식 코드BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion
https://github.com/sen-mao/3di2i-translation
공식 코드https://github.com/sergiuoprea/hgan
공식 코드https://github.com/shahaf1313/procst
공식 코드ProCST: Boosting Semantic Segmentation Using Progressive Cyclic Style-Transfer
https://github.com/sharif-apu/twostageHDR_NTIRE21
공식 코드A Two-stage Deep Network for High Dynamic Range Image Reconstruction
https://github.com/shendu-sw/PIRL
공식 코드https://github.com/shenzheng2000/tpsence
공식 코드TPSeNCE: Towards Artifact-Free Realistic Rain Generation for Deraining and Object Detection in Rain
https://github.com/sheqi/GAN_Review
공식 코드Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy
https://github.com/shinshoji01/Style-Restricted_GAN
공식 코드https://github.com/sian-wusidi/stegogan
공식 코드StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation
https://github.com/sihanxu/ace
공식 코드ACE: Zero-Shot Image to Image Translation via Pretrained Auto-Contrastive-Encoder
https://github.com/simontomaskarlsson/GAN-MRI
공식 코드https://github.com/singlezombie/afldm
공식 코드Alias-Free Latent Diffusion Models:Improving Fractional Shift Equivariance of Diffusion Latent Space
https://github.com/siyuhuang/latent-space-anchoring
공식 코드Domain-Scalable Unpaired Image Translation via Latent Space Anchoring
https://github.com/sj-li/dp_gan
공식 코드Dual Pyramid Generative Adversarial Networks for Semantic Image Synthesis
https://github.com/skrmanne/3dlut_srgb_wb
공식 코드WB LUTs: Contrastive Learning for White Balancing Lookup Tables
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.