Introduces an LRU-based network with semantic modulation that claims to outperform prior super-resolution methods at similar computational cost.
To match the batch size with previous works [22, 49, 55], we doubled it compared to the classic SR setting, while keeping all other training strategies identical to those of LSM-S
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Linear Recurrent Unit with Semantic Modulation for Image Super-Resolution
Introduces an LRU-based network with semantic modulation that claims to outperform prior super-resolution methods at similar computational cost.