Sep 4, 2023 · In this paper, we introduce a Channel-Guidance Network (CGNet) that leverages the benefits of RAW images for over-exposure correction.

We used the Channel-Guidance Network (CGNet) model for overexposure correction. Since the input of. CGNet is RGGB four-channel, the training data is converted ...

We develop a new RAW-based non-green channel guidance strategy to maximize the utilization of useful information from red and blue channels and exploit the ...

Experiments on our RAW-sRGB datasets validate the advantages of our RAW-based channel guidance strategy and proposed CGNet over state-of-the-art sRGB-based ...

Sep 4, 2023 · In this paper, we introduce a Channel-Guidance Network (CGNet) that leverages the benefits of RAW images for over-exposure correction. The CGNet ...

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Abstract. In this technical report, we briefly introduce the solution of the ”LiGoxin” team in the Raw. Image Based Over-Exposure Correction Challenge.

Most existing methods for over-exposure in image correction are developed based on sRGB images, which can result in complex and non-linear degradation due ...

[a] Y. Fu et al., "Raw Image Based Over-Exposure Correction Using Channel-Guidance Strategy," in IEEE Transactions on Circuits and Systems for Video Technology ...

An extensive collection of RAW/sRGB images rendered with realistic over-exposure errors and corresponding accurately exposed ground truth images.