Search Results for author:
Found 13 papers, 2 papers with code
Differentiable Sensor Layouts for End-to-End Learning of Task-Specific Camera Parameters
The success of deep learning is frequently described as the ability to train all parameters of a network on a specific application in an end-to-end fashion.
Neural Volume Super-Resolution
This allows us to super-resolve the 3D scene representation by applying 2D convolutional networks on the 2D feature planes.
Light Field Implicit Representation for Flexible Resolution Reconstruction
consists of a feature extractor and a decoder which are trained on a dataset of light field patches.
A Generative Model for Generic Light Field Reconstruction
We develop a generative model conditioned on the central view of the light field and incorporate this as a prior in an energy minimization framework to address diverse light field reconstruction tasks.
Energy Dissipation with Plug-and-Play Priors
In this paper we consider the combination of both approaches by projecting the outputs of a plug-and-play denoising network onto the cone of descent directions to a given energy.
Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction
Extracting the interpretable and physically meaningful parameters for such applications, however, requires solving an inverse problem in which a model function determined by these parameters needs to be fitted to the measured data.
Supervised Deep Kriging for Single-Image Super-Resolution
We propose a novel single-image super-resolution approach based on the geostatistical method of kriging.
A Bit Too Much? High Speed Imaging from Sparse Photon Counts
Recent advances in photographic sensing technologies have made it possible to achieve light detection in terms of a single photon.
Residuum-Condition Diagram and Reduction of Over-Complete Endmember-Sets
By plotting the residuum resulting from the unmixing and reconstruction and the condition number of various EM sets, the resulting diagram provides insight into the behavior of the spectral unmixing under a varying amount of endmembers (EMs).
Preoperative Volume Determination for Pituitary Adenoma
The most common sellar lesion is the pituitary adenoma, and sellar tumors are approximately 10-15% of all intracranial neoplasms.
A Comprehensive Multi-Illuminant Dataset for Benchmarking of the Intrinsic Image Algorithms
In this paper, we provide a new, real photo dataset with precise ground-truth for intrinsic image research.
Defocus Deblurring and Superresolution for Time-of-Flight Depth Cameras
Continuous-wave time-of-flight (ToF) cameras show great promise as low-cost depth image sensors in mobile applications.
Kinect Range Sensing: Structured-Light versus Time-of-Flight Kinect
Recently, the new Kinect One has been issued by Microsoft, providing the next generation of real-time range sensing devices based on the Time-of-Flight (ToF) principle.
