DWTA-Net is a two-stage recurrent neural network for low-light video enhancement that combines Mamba-based local restoration with dynamic optical-flow-guided temporal aggregation and a texture-adaptive loss to suppress extreme noise.
Retinexformer: One-stage retinex-based transformer for low-light image enhance- ment,
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Dynamic Weight-based Temporal Aggregation for Low-light Video Enhancement Under Extreme Noise
DWTA-Net is a two-stage recurrent neural network for low-light video enhancement that combines Mamba-based local restoration with dynamic optical-flow-guided temporal aggregation and a texture-adaptive loss to suppress extreme noise.