Video Compressive Sensing
8 papers with code • 0 benchmarks • 0 datasets
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Latest papers with no code
Compression Ratio Learning and Semantic Communications for Video Imaging
In this article, we also investigate the data transmission methods for programmable sensors, where the performance of communication systems is evaluated by the reconstructed images or videos rather than the transmission of sensor data itself.
Sampling-Priors-Augmented Deep Unfolding Network for Robust Video Compressive Sensing
Video Compressed Sensing (VCS) aims to reconstruct multiple frames from one single captured measurement, thus achieving high-speed scene recording with a low-frame-rate sensor.
Hierarchical Interactive Reconstruction Network For Video Compressive Sensing
Deep network-based image and video Compressive Sensing(CS) has attracted increasing attentions in recent years.
Motion-aware Dynamic Graph Neural Network for Video Compressive Sensing
Video snapshot compressive imaging (SCI) utilizes a 2D detector to capture sequential video frames and compresses them into a single measurement.
Revisit Dictionary Learning for Video Compressive Sensing under the Plug-and-Play Framework
Aiming at high-dimensional (HD) data acquisition and analysis, snapshot compressive imaging (SCI) obtains the 2D compressed measurement of HD data with optical imaging systems and reconstructs HD data using compressive sensing algorithms.
CSMCNet: Scalable Video Compressive Sensing Reconstruction with Interpretable Motion Estimation
Most deep network methods for compressive sensing reconstruction suffer from the black-box characteristic of DNN.
Reinforcement Learning for Adaptive Video Compressive Sensing
We apply reinforcement learning to video compressive sensing to adapt the compression ratio.
Generative Models for Low-Dimensional Video Representation and Compressive Sensing
In the context of compressive sensing, if the unknown image belongs to the range of a pretrained generative network, then we can recover the image by estimating the underlying compact latent code from the available measurements.
Video Compressive Sensing for Spatial Multiplexing Cameras using Motion-Flow Models
In this paper, we propose the CS multi-scale video (CS-MUVI) sensing and recovery framework for high-quality video acquisition and recovery using SMCs.
Video Compressive Sensing for Dynamic MRI
We apply this framework to accelerate the acquisition process of dynamic MRI and show it achieves the best reconstruction accuracy with the least computational time compared with existing algorithms in the literature.
