SOTAVerified

Colorization

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

Papers

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Showing 1–10 of 367 papers

TitleStatusHype
MTSIC: Multi-stage Transformer-based GAN for Spectral Infrared Image Colorization—0
Self-supervised Feature Extraction for Enhanced Ball Detection on Soccer Robots—0
Exploiting the Exact Denoising Posterior Score in Training-Free Guidance of Diffusion Models—0
SSIMBaD: Sigma Scaling with SSIM-Guided Balanced Diffusion for AnimeFace ColorizationCode0
Restoring Real-World Images with an Internal Detail Enhancement Diffusion Model—0
Leveraging the Powerful Attention of a Pre-trained Diffusion Model for Exemplar-based Image ColorizationCode0
Controllable Image Colorization with Instance-aware Texts and Masks—0
ColorVein: Colorful Cancelable Vein Biometrics—0
Cobra: Efficient Line Art COlorization with BRoAder References—0
Digital Staining with Knowledge Distillation: A Unified Framework for Unpaired and Paired-But-Misaligned DataCode0
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All datasetsImageNet valImageNet ctest10k

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1cGANFID-5K24.41—Unverified
2PixColorFID-5K24.32—Unverified
3ColtranFID-5K19.37—Unverified
4PaletteFID-5K15.78—Unverified