Spectral Reconstruction
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Benchmarks
Most implemented
Enhanced Deep Residual Networks for Single Image Super-Resolution
Restormer: Efficient Transformer for High-Resolution Image Restoration
Learning Enriched Features for Real Image Restoration and Enhancement
Multi-Stage Progressive Image Restoration
Papers
Learning Spatial-Spectral Refinement and Calibrating Complementary Observations for Hyperspectral Image Super-Resolution
Hyperspectral and multispectral image fusion (HMIF) aims to reconstruct a high-resolution hyperspectral image (HR-HSI) by combining the fine spatial details of a high-resolution multispectral image (HR-MSI) with the rich…
Spectral ReconstructionImage Super-ResolutionSemantic SegmentationSimulation-to-real transfer learning for infrared spectroscopic chemical sensing and analysis from molecules to complex samples
Infrared (IR) spectroscopy is widely used for chemical sensing, but extracting reliable chemical information from spectra remains challenging. Conventional interpretation is labor-intensive, relies on prior knowledge and…
Spectral ReconstructionTransfer LearningDual-Domain Manifold Modeling for Hyperspectral Image Fusion
Achieving a coherent integration of spectral richness and spatial fidelity remains a central objective in hyperspectral image fusion. However, existing hyperspectral image fusion methods struggle to effectively model geo…
Representation LearningSpectral ReconstructionNAC: Neural Action Codec for Vision-Language-Action Models
Vision-language-action (VLA) models rely on discrete action tokenizers to bridge continuous robot control and autoregressive sequence modeling, yet existing tokenizers often trade off between compression, latency, and do…
Spectral ReconstructionPF-Trans: Physics-Embedded Frequency-Aware Transformer for Spectral Reconstruction
Snapshot Broadband Filter Array (BFA) imaging provides high light throughput for spectral reconstruction but introduces severe spectral aliasing due to complex modulation. Current deep learning approaches, limited to spa…
Spectral ReconstructionAnyBand-Diff: A Unified Remote Sensing Image Generation and Band Repair Framework with Spectral Priors
Existing diffusion models have made significant progress in generating realistic images. However, their direct adaptation to remote sensing imagery often disregards intrinsic physical laws. This oversight frequently lead…
Spectral ReconstructionImage Generation