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Top Star Repos
9615Code and data for paper "Deep Photo Style Transfer": https://arxiv.org/abs/1703.07511
4715Matlab code for machine learning algorithms in book PRML
4545OpenFace – a state-of-the art tool intended for facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation.
3503Matlab/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 get you started.
2421Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks
2072OpenTLD 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
2030R-CNN: Regions with Convolutional Neural Network Features
1913Transport coordinate between earth(WGS-84) and mars in china(GCJ-02).
1316This 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/
1274Class Activation Mapping
1200R-FCN: Object Detection via Region-based Fully Convolutional Networks
1078This repo is specially created for all the work done my me as a part of Coursera's Machine Learning Course.
1061Tiny Face Detector, CVPR 2017
952This program converts MATLAB®/Octave figures to TikZ/pgfplots figures for smooth integration into LaTeX.
929Bayesian Program Learning model for one-shot learning
866Omniglot data set for one-shot learning
820A MATLAB toolbox for exporting publication quality figures
770Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)
745my octave exercises for 2011 stanford machine learning class, posted after the due date of course
743Piotr's Image & Video Matlab Toolbox
703Original Caffe Version for LightCNN-9. Highly recommend to use PyTorch Version (https://github.com/AlfredXiangWu/LightCNN)
692Memory consumption and FLOP count estimates for convnets
673Structured Edge Detection Toolbox
651Resources about activity recognition-行为识别资料
1Bad weather conditions can reduce visibility on images acquired outdoors, decreasing their visual qual- ity. The image processing task concerned with the mitigation of this effect is known as image dehaz- ing. In this paper we present a new image dehazing technique that can remove the visual degradation due to haze without relying on the inversion of a physical model of haze formation, but respecting its main underlying assumptions. Hence, the proposed technique avoids the need of estimating depth in the scene, as well as costly depth map refinement processes. To achieve this goal, the original hazy image is first artificially under-exposed by means of a sequence of gamma-correction operations. The resulting set of multiply-exposed images is merged into a haze-free result through a multi-scale Laplacian blend- ing scheme. A detailed experimental evaluation is presented in terms of both qualitative and quantitative analysis. The obtained results indicate that the fusion of artificially under-exposed images can effectively remove the effect of haze, even in challenging situations where other current image dehazing techniques fail to produce good-quality results.
0The purpose of this project is to continuously classify non-steady-state activities of participants using LSTM and LDA. Biomechanical data including linear acceleration and angular velocity of upper and lower-body segments were extracted from motion data and were used as system inputs.
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