https://github.com/vgangal101/VGG_models
Very Deep Convolutional Networks for Large-Scale Image Recognition
Papers with Code 아카이브
Image-to-Image Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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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/vgangal101/resnet_models
https://github.com/vict0rsch/ArxivTools
https://github.com/vict0rsch/PaperMemory
https://github.com/vict0rsch/arxiv-pdf-abs
https://github.com/victespinoza/NeuralStyleTransfer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vietanhdev/open-adas
https://github.com/vietdhoang/resnet-18
https://github.com/vihari/crossgrad
https://github.com/viibridges/crossnet
https://github.com/vinay-EIP/EIP-session-5-assignment
https://github.com/vineeths96/Gradient-Compression
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vineeths96/heterogeneous-systems
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/vinod377/STN-OCR
https://github.com/vinod377/STN-OCR-Tensorflow
https://github.com/vinthony/s2crnet-demos
Spatial-Separated Curve Rendering Network for Efficient and High-Resolution Image Harmonization
https://github.com/vinx-2105/madgan-degan
https://github.com/vipermu/ganimation
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/vita-epfl/rock-pytorch
https://github.com/vlievin/Unet
https://github.com/vpsg-research/waveguard
GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/vwegn/dm
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wallacemplira/ganhopper
GANHopper: Multi-Hop GAN for Unsupervised Image-to-Image Translation
https://github.com/wangyu33/rStarGAN-master
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
https://github.com/wangyuan249/Mymmt767
https://github.com/wasilone11/ICPR-RIP-2024
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/waterdisappear/nudt4mstar
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/weipeng0703/Pix2Pix_MindSpore_For_PaperWithCode/tree/main/Pix2Pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/wen227/Pokemon_Classification
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wentao99/pix2pixHD
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/wenxinxu/resnet-in-tensorflow
https://github.com/wenxinxu/resnet_in_tensorflow
https://github.com/wfwf10/feature-based-federated-transfer-learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/wileyw/DeepLearningDemos
Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy
https://github.com/willylulu/RelGAN
RelGAN: Multi-Domain Image-to-Image Translation via Relative Attributes
https://github.com/winfried-loetzsch/deep-hist
DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.