https://github.com/hcygeorge/aoi_defect_detection
Very Deep Convolutional Networks for Large-Scale Image Recognition
Papers with Code 아카이브
Image-to-Image Translation
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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/hello-world-cc/starGANv1-Pytorch
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
https://github.com/henriquemeloo/cat-dog-image-classifier
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/hero9968/pix2pix-tensorflow
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/hershd23/ObjectLocalizer
https://github.com/hieu2906090/deep-learning-in-js
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/hmatty/stylized-neural-painting
https://github.com/hollance/VGGNet-Metal
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/holstgr-kaust/keras-tutorials
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/hongkunsun/paratranscnn
https://github.com/hongyi-zhang/Fixup
https://github.com/honzaMaly/cyclegan-style-transfer
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/horse007666/ResNet
https://github.com/hsd1503/resnet1d
https://github.com/hsinyilin19/resnetvae
https://github.com/hthoai/UI2IT
https://github.com/huawei-noah/Pruning
https://github.com/hujinsen/pytorch-StarGAN-VC
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/humansensinglab/cycle-diffusion
Unifying Diffusion Models' Latent Space, with Applications to CycleDiffusion and Guidance
https://github.com/hustic/TinyImageSet
https://github.com/hustvl/sparseinst
https://github.com/hwang9u/hum2Guitar
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/hx19940102/Image-Segmentation-based-on-FCN
https://github.com/hycis/TensorGraph
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/hyn2028/llm-cxr
https://github.com/hysts/pytorch_resnet
https://github.com/hysts/pytorch_resnet_preact
https://github.com/hytseng0509/DRIT_hr
Diverse Image-to-Image Translation via Disentangled Representations
https://github.com/hz2538/iot_JennyGo
https://github.com/iArunava/ResNet
https://github.com/icon-lab/pflsynth
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/ika-rwth-aachen/etsi_its_messages
https://github.com/imkoushik22/Walmart-Hackathon
https://github.com/interdigitalinc/featurestyleencoder
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
https://github.com/interestingzhuo/foodretreival
https://github.com/isaacschaal/SG_training
Very Deep Convolutional Networks for Large-Scale Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.