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Found 3 papers, 2 papers with code
Modeling sRGB Camera Noise with Normalizing Flows
The nonlinear steps on the ISP culminate in a significantly more complex noise distribution in the sRGB domain and existing raw-domain noise models are unable to capture the sRGB noise distribution.
Noise2NoiseFlow: Realistic Camera Noise Modeling without Clean Images
This paper proposes a framework for training a noise model and a denoiser simultaneously while relying only on pairs of noisy images rather than noisy/clean paired image data.
Zero-shot Learning with Class Description Regularization
The purpose of generative Zero-shot learning (ZSL) is to learning from seen classes, transfer the learned knowledge, and create samples of unseen classes from the description of these unseen categories.
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