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This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."
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 …
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks
R-CNN: Regions with Convolutional Neural Network Features
OpenTLD is an open source library for real-time 2D tracking of a single object in video. This repository is no longer under development. For latest version see: http://www.tldvision.com/tld2.html
Robotics Toolbox for MATLAB
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.vi…
R-FCN: Object Detection via Region-based Fully Convolutional Networks
Apply and save color schemes in MATLAB with ease.
Original Caffe Version for LightCNN-9. Highly recommend to use PyTorch Version (https://github.com/AlfredXiangWu/LightCNN)
Collection and a development kit of matlab mex functions for OpenCV library
Matlab toolbox for Geometry Processing.
Code release for "Detect to Track and Track to Detect", ICCV 2017
An Experimental Implementation of Face Verification, 96.8% on LFW.
Ensemble of Exemplar-SVMs for Object Detection and Beyond
A Library of ADMM for Sparse and Low-rank Optimization
Learning Rich Features from RGB-D Images for Object Detection and Segmentation
Manopt, a Matlab toolbox for optimization on manifolds
DeconvNet : Learning Deconvolution Network for Semantic Segmentation
Computer vision feature extraction toolbox for image classification
LSTM-MATLAB is Long Short-term Memory (LSTM) in MATLAB, which is meant to be succinct, illustrative and for research purpose only. It is accompanied with a paper for reference: Revisit Long Short-T…
[CVPR'16] Staple: Complementary Learners for Real-Time Tracking"
Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views