robinkk4

3d_ultrasonic_scanner

An ultrasonic 3D scanner

3DCS

Three-dimensional compressive sensing algorithms

3dmatch-toolbox

3DMatch reference implementation.

A-Low-rank-Tensor-Dictionary-Learning-Method-for-Multi-spectral-Images-Denoising

Code is available on https://www.dropbox.com/s/80ltjrxr2v9maeg/LTDL.zip?dl=0

asp

Active-Set Pursuit: an active-set solver for basis pursuit and related sparse optimization problems

Beamerscope_TENSORFLOW

This creates a Tensorflow Graph for the automaized illumination detection.

BlueNoise

A SciPy implementation of the void-and-cluster method for generation of blue noise textures with arbitrary dimension.

confocal-diffuse-tomography

Code and data for "Three-dimensional imaging through scattering media based on confocal diffuse tomography"

specularity-removal

Specularity detection and removal for endoscopic images/videos.

robinkk4/dso_ros

ROS wrapper for dso

robinkk4/specularity-removal

Specularity detection and removal for endoscopic images/videos.

robinkk4/Beamerscope_TENSORFLOW

This creates a Tensorflow Graph for the automaized illumination detection.

robinkk4/ldd4

robinkk4/falkolib

A library containing keypoint detectors for the stable detection of interest points in laser measurements and two descriptors for robust associations.

robinkk4/crfasrnn

This repository contains the source code for the semantic image segmentation method described in the ICCV 2015 paper: Conditional Random Fields as Recurrent Neural Networks. http://crfasrnn.torr.vision/

robinkk4/Depth-Estimation-using-CNN

Simple depth maps obtained by using CNN

robinkk4/pySPIRALTAP

Sparse Poisson Intensity Reconstruction ALgorithms

robinkk4/BlueNoise

A SciPy implementation of the void-and-cluster method for generation of blue noise textures with arbitrary dimension.

robinkk4/3dmatch-toolbox

3DMatch reference implementation.

robinkk4/3DCS

Three-dimensional compressive sensing algorithms

robinkk4/ConvDicLearnTensorFactor

Tensor methods have emerged as a powerful paradigm for consistent learning of many latent variable models such as topic models, independent component analysis and dictionary learning. Model parameters are estimated via CP decomposition of the observed higher order input moments. However, in many domains, additional invariances such as shift invariances exist, enforced via models such as convolutional dictionary learning. In this paper, we develop novel tensor decomposition algorithms for parameter estimation of convolutional models. Our algorithm is based on the popular alternating least squares method, but with efficient projections onto the space of stacked circulant matrices. Our method is embarrassingly parallel and consists of simple operations such as fast Fourier transforms and matrix multiplications. Our algorithm converges to the dictionary much faster and more accurately compared to the alternating minimization over filters and activation maps.

robinkk4/JEDI

Joint Estimation of Dictionary and Image (from compressive samples)

robinkk4/Optimized-Sensing-Matrices-for-Compressed-Sensing

Computer vision project to optimize the conventional random Gaussian Sensing Matrix for better reconstruction

robinkk4/EveryDaySport

从昨天开始做一个健康的程序员。

robinkk4/FreeRtos-Labs

robinkk4/RIDL-Hex

Rotation Invariant Dictionary Learning using Hexagonal grid

robinkk4/TVAL3D

This is an update in 3D-reconstruction of the MATLAB's code TVAL3 written by Chengbo Li

robinkk4/OpenPilot

OpenPilot Github Mirror

robinkk4/tessa

A collection of Python code for calculation of various texture features