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Found 7 papers, 5 papers with code
BIRNAT: Bidirectional Recurrent Neural Networks with Adversarial Training for Video Snapshot Compressive Imaging
This measurement and the modulation masks are fed into our Recurrent Neural Network (RNN) to reconstruct the desired high-speed frames.
End-to-End Low Cost Compressive Spectral Imaging with Spatial-Spectral Self-Attention
Coded aperture snapshot spectral imaging (CASSI) is an effective tool to capture real-world 3D hyperspectral images.
Ranked #7 on
Spectral Reconstruction
on Real HSI
Key Information Retrieval to Classify the Unstructured Data Content of Preferential Trade Agreements
To address this issue, we introduce a novel approach to long-text classification and prediction.
Block Modulating Video Compression: An Ultra Low Complexity Image Compression Encoder for Resource Limited Platforms
We consider the image and video compression on resource limited platforms.
Modeling Mask Uncertainty in Hyperspectral Image Reconstruction
Recently, hyperspectral imaging (HSI) has attracted increasing research attention, especially for the ones based on a coded aperture snapshot spectral imaging (CASSI) system.
Self-supervised Neural Networks for Spectral Snapshot Compressive Imaging
In this paper, inspired by the untrained neural networks such as deep image priors (DIP) and deep decoders, we develop a framework by integrating DIP into the plug-and-play regime, leading to a self-supervised network for spectral SCI reconstruction.
GAP-net for Snapshot Compressive Imaging
The hardware encoder typically consists of an (optical) imaging system designed to capture {compressed measurements}.
