Stars
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to …
R-CNN: Regions with Convolutional Neural Network Features
Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
Various hashing methods for image retrieval and serves as the baselines
Object detection system using deformable part models (DPMs) and latent SVM (voc-release5). You may want to use the latest tarball on my website. The github code may include code changes that have n…
An Experimental Implementation of Face Verification, 96.8% on LFW.
Ensemble of Exemplar-SVMs for Object Detection and Beyond
NormFace: L2 HyperSphere Embedding for Face Verification, 99.21% on LFW
Multiscale Combinatorial Grouping - Object Proposals and Segmentation
The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at <http://www.cs.cmu.edu/~aayushb/pixelNet/>.
Matlab Code for Restricted/Deep Boltzmann Machines and Autoencoders
A MatConvNet-based implementation of the Fully-Convolutional Networks for image segmentation
Repository containing wrapper to obtain various object proposals easily
A VGG practical on convolutional neural networks
Weakly Supervised Deep Detection Networks (CVPR 2016)
Deep feature pyramids for various computer vision algorithms (DPMs, pyramid R-CNN, etc.)
Code for Implementation, Inference, and Learning of Bayesian and Markov Networks along with some practical examples.
The Matlab implementation of Supervised Descent Method (SDM) for Face Alignment.
Deep Filter Banks for Texture Recognition, Description and Segmentation (CVPR15)
Hamming Distance Metric Learning with Non-linear Projection
Cascade Object Detection with Deformable Part Models – Add-on package for voc-release4.01
Implementation of Semantic Hashing. Modified from Ruslan Salakhutdinov and Geoff Hinton's code of training Deep AutoEncoder
Libraries for training and testing Continuous Conditional Neural Fields with a number of sample problems and other baselines.
Image inpainting using coherency senstitive hashing