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/laclark/cuneiform_lineart
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/lancerane/Adversarial-domain-adaptation
https://github.com/layumi/DG-Net
Joint Discriminative and Generative Learning for Person Re-identification
https://github.com/layumi/Person_reID_baseline_pytorch
Joint Discriminative and Generative Learning for Person Re-identification
https://github.com/leebebeto/pytorch-implementation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/leehomyc/cyclegan-1
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/leemathew1998/GradientWeight
https://github.com/leemathew1998/RG
https://github.com/leenaali1114/Hierarchical-Image-Clustering---Unsupervised-Learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/leffff/FlowModels
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
https://github.com/leffff/flow-matching-experiments
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
https://github.com/leob03/E2E_Object_Pose_Estimator
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/leongatys/DeepTextures
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/leongatys/PytorchNeuralStyleTransfer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/lh-wang/ACC
Virtual to Real Reinforcement Learning for Autonomous Driving
https://github.com/lianqing11/pycda
https://github.com/libreai/neural-painters-x
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/lightning-uq-box/lightning-uq-box
https://github.com/linainsaf/RESNET50_PNEUMONIA_DETECTION
https://github.com/linxi159/GAN-training-tricks
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/linxi159/Tips-and-tricks-to-train-GANs
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/liorfrenkel1992/SB-GAN
https://github.com/liqunchen0606/triangle-gan
https://github.com/liuliuliu11/pixel2style2pixel-liu
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
https://github.com/liuyao12/ConvNets-PDE-perspective
https://github.com/liuzeyuMr/CycleGAN-TensorFlow-master
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/lixihan/Resnet
https://github.com/lixixibj/forecasting-with-time-series-imaging
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/lixixibj/tsImage-forecasting
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ljy-hy/mentormix_pytorch
https://github.com/lkeonwoo94/DL_cv-mdt_NVIDIA_Cert_Course_StudyPI
https://github.com/lkhphuc/Anomaly-BiGAN
https://github.com/lkhphuc/Anomaly-XRay-GANs
https://github.com/lllyasviel/controlnet
MaskSketch: Unpaired Structure-guided Masked Image Generation
https://github.com/lornatang/cyclegan-pytorch
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.