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/ermolenkodev/da-ssd
https://github.com/ermongroup/alignflow
AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows
https://github.com/ewinata/CIFAR-10
https://github.com/fL0n9/SKFAC-MindSpore
https://github.com/fabioasdias/ubao
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/fabiofumarola/ultrayolo
https://github.com/fabxy/accessibilityCV
https://github.com/facebook/fb.resnet.torch
https://github.com/facebookarchive/fb.resnet.torch
https://github.com/facebookresearch/DomainBed
https://github.com/facebookresearch/detectron
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/facebookresearch/hiera
https://github.com/facebookresearch/pycls
https://github.com/facebookresearch/stochastic_gradient_push
https://github.com/facundoq/transformational_measures_experiments
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/fastai/fastai
https://github.com/fchollet/deep-learning-models
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/fdasilva59/Pix2Pix-Kubeflow-Demo
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/feipanir/intrada
Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision
https://github.com/felixgwu/img_classification_pk_pytorch
https://github.com/fengredrum/cnn-xla
https://github.com/francislata/Sign-Language-Digits-CNN
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/fraxea/pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/fuenwang/CVFX-hw1
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/fungtion/DANN
https://github.com/fuqinshen/UGATIT-pytorch
https://github.com/g61412333/pix2pix-tensorflow
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/gabrieletiboni/Domain-adaptation-on-PACS-dataset
https://github.com/gagan16/Cyclegan-tensorflow
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/ganslate-team/ganslate
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/gatheluck/Stronghold
https://github.com/gcr/torch-residual-networks
https://github.com/gcwl/pytorch-cyclegan
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/gcwl/pytorch-pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/gentlezhu/shift-robust-gnns
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.