https://github.com/humblefool01/Image-Colourization
Deep Koalarization: Image Colorization using CNNs and Inception-ResNet-v2
Papers with Code 아카이브
Colorization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 2
- 보존된 평가 기록
- 5
Colorization is the process of adding plausible color information to monochrome photographs or videos. Colorization is a highly undetermined problem, requiring mapping a real-valued luminance image to a three-dimensional color-valued one, that has not a unique solution.
Source: ChromaGAN: An Adversarial Approach for Picture Colorization
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hyliu/piggyback-color
Improved Diffusion-based Image Colorization via Piggybacked Models
https://github.com/hyn2028/tpdm
Score-Based Generative Modeling through Stochastic Differential Equations
https://github.com/hyperparameters/tracking_via_colorization
https://github.com/icon-lab/pflsynth
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/icyeyeball/Peitent
Style Transfer for Anime Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN
https://github.com/intuitive-robots/beso
Score-Based Generative Modeling through Stochastic Differential Equations
https://github.com/ipc-lab/deepjscc-diffusion
Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model
https://github.com/itsuki8914/pix2pix-automaticColorization
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/ivankunyankin/pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/iver56/automatic-video-colorization
https://github.com/jabir-zheng/TCD
https://github.com/jackaduma/CycleGAN-VC2
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/jaingaurav3/GAN-Hacks
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/jeniasivets/chromagan
ChromaGAN: Adversarial Picture Colorization with Semantic Class Distribution
https://github.com/jkcracker/colorization
https://github.com/jonryf/deep-learning-image-colorization-using-gan
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/json9512/sonarToimage
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/junhsss/consistency-models
https://github.com/jxcodetw/Adversarial-Colorization-Of-Icons-Based-On-Structure-And-Color-Conditions
Adversarial Colorization Of Icons Based On Structure And Color Conditions
https://github.com/k-Petropoulos/colorization
https://github.com/kdhRick2222/Exposure-slot
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse Problems
https://github.com/kingcheng2000/GAN
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/kkhosla96/cs231n-project
Deep Koalarization: Image Colorization using CNNs and Inception-ResNet-v2
https://github.com/komeiharada/learn_DL_together
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/kuan-wang/The_Bilateral_Solver
https://github.com/kulkarnikeerti/Image-to-image-translation-using-cGAN
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/kylelo/roofdiffusion
https://github.com/laclark/cuneiform_lineart
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/leemathew1998/GradientWeight
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/leemathew1998/RG
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/leon-schi/ColorNet
https://github.com/liaopeiyuan/pndm
Score-Based Generative Modeling through Stochastic Differential Equations
https://github.com/linxi159/GAN-training-tricks
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/linxi159/Tips-and-tricks-to-train-GANs
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/lllyasviel/style2paints
Style Transfer for Anime Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.