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/mathilde-b/SRDA
A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban Scenes
https://github.com/matlab-deep-learning/pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/matt-bendel/pcagan
A Regularized Conditional GAN for Posterior Sampling in Image Recovery Problems
https://github.com/matteodalessio/CycleGAN-android
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/maxwelltsai/DeepGalaxy
https://github.com/mbsariyildiz/resnet-pytorch
https://github.com/mcaseyrehm/pix2pixColab
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/mcd4874/neurips_competition
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
https://github.com/mdda/deep-learning-models
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/megvii-research/basecls/tree/main/zoo/public/resnet
https://github.com/megvii-research/basecls/tree/main/zoo/public/vgg
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mehdibnc/Cycle-GAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/mehdidc/any2any
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/mengweiren/segmentation-renormalized-harmonization
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/mgonzalezrivero/reef_learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mhagiwara/nanigonet
https://github.com/michael-hoss/rolling-review-updates
A Review of Testing Object-Based Environment Perception for Safe Automated Driving
https://github.com/michalgeyer/pnp-diffusers
Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation
https://github.com/michiel-j/DANN-two-moons-PyTorch
https://github.com/mickan123/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/microsoft/CoCosNet
Cross-domain Correspondence Learning for Exemplar-based Image Translation
https://github.com/microsoft/fb.resnet.torch
https://github.com/miguel-rodrigo/dot-csv-pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/mikekestemont/deepscript
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mikelasz/fair-psp
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
https://github.com/milenagazdieva/extremalneuraloptimaltransport
https://github.com/mindlab-ai/mindcv/blob/main/examples/train_cifar_dynamic.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/resnet.py
https://github.com/mindlab-ai/mindcv/blob/main/mindcv/models/vgg.py
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindslab-ai/hififace
Semantic Image Synthesis with Spatially-Adaptive Normalization
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet50_quant
https://github.com/mindspore-ai/models/tree/master/official/cv/resnet_thor
https://github.com/mindspore-ai/models/tree/master/official/cv/vgg16
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/mindspore-ai/models/tree/master/research/cv/CycleGAN
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.