Papers with Code 아카이브
Synthetic-to-Real Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Synthetic-to-real translation is the task of domain adaptation from synthetic (or virtual) data to real data.
<span style="color:grey; opacity: 0.6">( Image credit: CYCADA )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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/hiera
https://github.com/facebookresearch/pycls
https://github.com/facebookresearch/stochastic_gradient_push
https://github.com/facundoq/transformational_measures_experiments
https://github.com/fastai/fastai
https://github.com/fchollet/deep-learning-models
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/gabrieletiboni/Domain-adaptation-on-PACS-dataset
https://github.com/gatheluck/Stronghold
https://github.com/gcr/torch-residual-networks
https://github.com/gentlezhu/shift-robust-gnns
https://github.com/glouppe/info8010-deep-learning
https://github.com/godwinrayanc/YOLOv1-Pytorch
https://github.com/google/flax/tree/master/examples/imagenet
https://github.com/gpleiss/limits_of_large_width
https://github.com/greatsharma/DeepLearning-Papers-Implementation
https://github.com/gundeep15/SCD_AI_Project
https://github.com/guy-oren/DIRT-OST
Diverse Image-to-Image Translation via Disentangled Representations
https://github.com/haonanguo/remote-sensing-chatgpt
https://github.com/hershd23/ObjectLocalizer
https://github.com/hongkunsun/paratranscnn
https://github.com/hongyi-zhang/Fixup
https://github.com/horse007666/ResNet
https://github.com/hsd1503/resnet1d
https://github.com/hsinyilin19/resnetvae
https://github.com/hustic/TinyImageSet
https://github.com/hustvl/sparseinst
https://github.com/hx19940102/Image-Segmentation-based-on-FCN
https://github.com/hycis/TensorGraph
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.