Papers with Code 아카이브
Synthetic Data Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 2
- 보존된 평가 기록
- 4
The generation of tabular data by any means possible.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/clberube/ip-vae
https://github.com/cmitash/physim-dataset-generator
https://github.com/code-implementation1/Code8/tree/main/SinGAN
SinGAN-Seg: Synthetic training data generation for medical image segmentation
https://github.com/croesuslab/RCTGAN
https://github.com/cryu854/SinGAN
https://github.com/cvzoya/visuallydata
Synthetically Trained Icon Proposals for Parsing and Summarizing Infographics
https://github.com/cwolfbrandt/csk
https://github.com/dabsdamoon/Anime-Colorization
https://github.com/dabsdamoon/Anime-Colorization-v0.2
https://github.com/dagrate/gan_network
https://github.com/daheyinyin/wgan
https://github.com/daheyinyin/wgan_gp
https://github.com/divyam25/Oh-My-GAN
https://github.com/donand/GAN_pytorch
https://github.com/dylanell/conditional-wgan
https://github.com/dylanell/wasserstein-gan
https://github.com/ebarsoum/hpgan
https://github.com/eriklindernoren/Keras-GAN
https://github.com/eriklindernoren/PyTorch-GAN
https://github.com/eth-sri/llm-anonymization
https://github.com/facebookresearch/multiface
Learning Compositional Radiance Fields of Dynamic Human Heads
https://github.com/fangyiyu/gnpassgan
https://github.com/findaheng/Scenic
Scenic: A Language for Scenario Specification and Scene Generation
https://github.com/fqnchina/CEILNet
A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing
https://github.com/franroldans/tfm-franroldan-wav2pix
https://github.com/g4vrel/simple_ml/tree/main/WGAN
https://github.com/goldhuang/SRGAN-PyTorch
https://github.com/google/burst-denoising
https://github.com/henry32144/wgan-gp-tensorflow
https://github.com/hse-cs/probaforms
https://github.com/huybik/GAN-Experiments-Pytorch
https://github.com/huybik/GANs-Pytorch
https://github.com/instructlab/instructlab
https://github.com/itsuki8914/wgan-gp-TensorFlow
https://github.com/ja3067/wgan-pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.