HICNet is a reference-guided exposure correction network that distills images into illumination embeddings, uses their differences to drive FiLM-based modulation and photometric channel rebalancing, and employs cross-batch contrastive loss, all trained without ground truth.
Experiment Settings Dataset.We evaluate our method on two datasets: the MSEC Dataset from [1]
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Learning Reference-Guided Exposure Correction with Hybrid Illumination Characteristics
HICNet is a reference-guided exposure correction network that distills images into illumination embeddings, uses their differences to drive FiLM-based modulation and photometric channel rebalancing, and employs cross-batch contrastive loss, all trained without ground truth.