A Mamba-based interactive state space model with cross-modal local scanning achieves competitive guided depth super-resolution performance at linear computational cost.
Restormer: Efficient transformer for high-resolution image restoration
3 Pith papers cite this work. Polarity classification is still indexing.
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The paper proposes the Degradation Frequency Curve (DFC) as an explicit spectral representation for quantifying degradations and develops a DFC-guided multi-scale restorer that achieves state-of-the-art performance on composite and real-world benchmarks.
TGPNet unifies denoising, cloud removal, shadow removal, deblurring, and SAR despeckling into one model via task-guided prompting and reports state-of-the-art results on a new multi-modal benchmark.
citing papers explorer
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Interactive State Space Model with Cross-Modal Local Scanning for Depth Super-Resolution
A Mamba-based interactive state space model with cross-modal local scanning achieves competitive guided depth super-resolution performance at linear computational cost.
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Degradation Frequency Curve: An Explicit Frequency-Quantified Representation for All-in-One Image Restoration
The paper proposes the Degradation Frequency Curve (DFC) as an explicit spectral representation for quantifying degradations and develops a DFC-guided multi-scale restorer that achieves state-of-the-art performance on composite and real-world benchmarks.
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Task-Guided Prompting for Unified Remote Sensing Image Restoration
TGPNet unifies denoising, cloud removal, shadow removal, deblurring, and SAR despeckling into one model via task-guided prompting and reports state-of-the-art results on a new multi-modal benchmark.