Papers Video Compressive Sensing
“Video Compressive Sensing” 태그가 달린 논문 20편 · 필터 해제
Towards Real-time Video Compressive Sensing on Mobile Devices
Video Snapshot Compressive Imaging (SCI) uses a low-speed 2D camera to capture high-speed scenes as snapshot compressed measurements, followed by a reconstruction algorithm to retrieve the high-speed video frames. The fa…
Compressive SensingKnowledge DistillationVideo Compressive SensingCompression Ratio Learning and Semantic Communications for Video Imaging
Camera sensors have been widely used in intelligent robotic systems. Developing camera sensors with high sensing efficiency has always been important to reduce the power, memory, and other related resources. Inspired by …
compressed sensingCompressive SensingSemantic CommunicationVideo Compressive SensingSampling-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. Although there have been impressive advance…
compressed sensingCompressive SensingSingle Particle AnalysisVideo Compressive SensingHierarchical Interactive Reconstruction Network For Video Compressive Sensing
Deep network-based image and video Compressive Sensing(CS) has attracted increasing attentions in recent years. However, in the existing deep network-based CS methods, a simple stacked convolutional network is usually ad…
Compressive SensingVideo Compressive SensingMotion-aware Dynamic Graph Neural Network for Video Compressive Sensing
Video snapshot compressive imaging (SCI) utilizes a 2D detector to capture sequential video frames and compress them into a single measurement. Various reconstruction methods have been developed to recover the high-speed…
Compressive SensingGraph Neural NetworkVideo Compressive SensingTwo-Stage is Enough: A Concise Deep Unfolding Reconstruction Network for Flexible Video Compressive Sensing
We consider the reconstruction problem of video compressive sensing (VCS) under the deep unfolding/rolling structure. Yet, we aim to build a flexible and concise model using minimum stages. Different from existing deep u…
Compressive SensingDemosaickingVideo Compressive SensingRevisit 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 s…
Compressive SensingDenoisingDictionary LearningSSIM+1A Simple and Efficient Reconstruction Backbone for Snapshot Compressive Imaging
The emerging technology of snapshot compressive imaging (SCI) enables capturing high dimensional (HD) data in an efficient way. It is generally implemented by two components: an optical encoder that compresses HD signals…
Compressive SensingComputational EfficiencyImage ReconstructionRetrieval+2CSMCNet: 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. In this paper, a deep neural network with interpretable motion estimation named CSMCNet is proposed. The n…
Compressive SensingMotion EstimationVideo Compressive SensingReinforcement Learning for Adaptive Video Compressive Sensing
We apply reinforcement learning to video compressive sensing to adapt the compression ratio. Specifically, video snapshot compressive imaging (SCI), which captures high-speed video using a low-speed camera is considered …
Compressive Sensingobject-detectionObject Detectionreinforcement-learning+3Memory-Efficient Network for Large-scale Video Compressive Sensing
Video snapshot compressive imaging (SCI) captures a sequence of video frames in a single shot using a 2D detector. The underlying principle is that during one exposure time, different masks are imposed on the high-speed …
Compressive SensingDemosaickingVideo Compressive SensingMetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing
To capture high-speed videos using a two-dimensional detector, video snapshot compressive imaging (SCI) is a promising system, where the video frames are coded by different masks and then compressed to a snapshot measure…
Compressive SensingGPUVideo Compressive SensingGenerative Models for Low-Dimensional Video Representation and Compressive Sensing
Generative priors have become highly effective in solving inverse problems including denoising, inpainting, and reconstruction from few and noisy measurements. With a generative model we can represent an image with a muc…
Compressive SensingDenoisingVideo Compressive SensingCSVideoNet: A Real-time End-to-end Learning Framework for High-frame-rate Video Compressive Sensing
This paper addresses the real-time encoding-decoding problem for high-frame-rate video compressive sensing (CS). Unlike prior works that perform reconstruction using iterative optimization-based approaches, we propose a …
Compressive SensingGPUVideo Compressive SensingDeepBinaryMask: Learning a Binary Mask for Video Compressive Sensing
In this paper, we propose a novel encoder-decoder neural network model referred to as DeepBinaryMask for video compressive sensing. In video compressive sensing one frame is acquired using a set of coded masks (sensing m…
Compressive SensingDecoderVideo Compressive SensingVideo ReconstructionDeep Fully-Connected Networks for Video Compressive Sensing
In this work we present a deep learning framework for video compressive sensing. The proposed formulation enables recovery of video frames in a few seconds at significantly improved reconstruction quality compared to pre…
Compressive SensingVideo Compressive SensingLiSens --- A Scalable Architecture for Video Compressive Sensing
The measurement rate of cameras that take spatially multiplexed measurements by using spatial light modulators (SLM) is often limited by the switching speed of the SLMs. This is especially true for single-pixel cameras w…
Compressive SensingVideo Compressive SensingVideo Compressive Sensing for Spatial Multiplexing Cameras using Motion-Flow Models
Spatial multiplexing cameras (SMCs) acquire a (typically static) scene through a series of coded projections using a spatial light modulator (e.g., a digital micro-mirror device) and a few optical sensors. This approach …
Compressive SensingOptical Flow EstimationVideo Compressive SensingVideo Compressive Sensing for Dynamic MRI
We present a video compressive sensing framework, termed kt-CSLDS, to accelerate the image acquisition process of dynamic magnetic resonance imaging (MRI). We are inspired by a state-of-the-art model for video compressiv…
Compressive SensingVideo Compressive SensingSpaRCS: Recovering low-rank and sparse matrices from compressive measurements
We consider the problem of recovering a matrix $\mathbf{M}$ that is the sum of a low-rank matrix $\mathbf{L}$ and a sparse matrix $\mathbf{S}$ from a small set of linear measurements of the form $\mathbf{y} = \mathcal{A}…
Compressive SensingMatrix CompletionVideo Compressive Sensing