8 citations · 25 across the 6 of their papers we have counts for
20 papers
Snapshot Compressive Imaging: Principle, Implementation, Theory, Algorithms and Applications
Xin Yuan, David J. Brady, Aggelos K. Katsaggelos
Capturing high-dimensional (HD) data is a long-term challenge in signal processing and related fields. Snapshot compressive imaging (SCI) uses a two-dimensional (2D) detector to ca…
An Adaptive Video Acquisition Scheme for Object Tracking and its Performance Optimization
Srutarshi Banerjee, Henry H. Chopp, Juan G. Serra +3
We present a novel adaptive host-chip modular architecture for video acquisition to optimize an overall objective task constrained under a given bit rate. The chip is a high resolu…
E3D: Event-Based 3D Shape Reconstruction
Alexis Baudron, Zihao W. Wang, Oliver Cossairt +1
3D shape reconstruction is a primary component of augmented/virtual reality. Despite being highly advanced, existing solutions based on RGB, RGB-D and Lidar sensors are power and d…
2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual Network
Haoyu Wei, Florian Schiffers, Tobias Würfl +4
Computed tomography is widely used to examine internal structures in a non-destructive manner. To obtain high-quality reconstructions, one typically has to acquire a densely sample…
Lossy Event Compression based on Image-derived Quad Trees and Poisson Disk Sampling
Srutarshi Banerjee, Zihao W. Wang, Henry H. Chopp +2
With several advantages over conventional RGB cameras, event cameras have provided new opportunities for tackling visual tasks under challenging scenarios with fast motion, high dy…
Examining the Benefits of Capsule Neural Networks
Arjun Punjabi, Jonas Schmid, Aggelos K. Katsaggelos
Capsule networks are a recently developed class of neural networks that potentially address some of the deficiencies with traditional convolutional neural networks. By replacing th…