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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/manoranjan03/PaperImplementations
https://github.com/maragori/DeepfakeForensics-v1
https://github.com/marload/ConvNets-TensorFlow2
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/martin220485/everybody_dance_now_pytorch
https://github.com/mashaan14/ADDA
https://github.com/mashaan14/ADDA-toy
https://github.com/mashaan14/DANN-toy
https://github.com/masoudnick/brain-tumor-mri-classification
https://github.com/mastanimahdi/pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/matakshay/Neural_Image_Caption_Generator
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
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.