Distributed compressive video sensing (DCVS) has great potential for signal acquisition and
processing in source-limited communication, eg, wireless video sensors networks, because …

Non-local similarity-based group sparse representation (GSR) has shown great potential in
image restoration. Considering the universal existing non-stationarity of natural images and …

Recent deep learning-based video compressed sensing (VCS) methods have achieved
promising results but still suffer from numerous hyper-parameters and inflexibility. This paper …

视频压缩感知在采集端资源受限的视频采集应用场景有重要研究意义. 重构算法是视频压缩感知
的关键技术, 基于多假设预测的“预测-残差重构” 框架具有良好的重构性能. 但现有的多假设预测 …

Compared with traditional video surveillance systems, wireless video sensor systems are
more suitable for emergency application scenarios, such as underground coal mine disaster …

Multihypothesis-based compressed video sensing scheme attracts wide attention in the
research of resource-constrained video application scenarios. However, high-accuracy …

现有视频压缩感知神经网络重构算法采用的光流对齐和可变形卷积对齐的运动补偿方式存在
误差积聚, 信息感知范围有限等问题, 极大地限制了其有效性和实用性. 为了在不引入额外参数的 …

The traditional video compressed sensing (VCS) algorithms have elegant theoretical
interpretability. However, the deterministic sparse transformation used in these algorithms …

Image compressed sensing networks based on deep learning have achieved promising
performance recently, which provides a new idea for Compressed Video Sensing (CVS). For …

A multihypothesis-based residual reconstruction scheme (MHRR) is presented in
compressed video sensing (CVS). The residual is first predicted by a novel multihypothesis …