Computer Vision Resources

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Computer Vision Resources

Published: 12 Sep 2015 Category: computer_vision

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Courses
Edge detection
Images Denoising
Deblur
Painting
Bag Of Words
Activity Recognition
License Plate Recognition
Image Retrieval
Image Summary
Image Retargeting/Editing
Image Editing
Image Inpaiting
Image Dithering
Image Enhancement
Image Resizing
Image Cloning
Image Compositing
Image Stylization
Image Haze Removal
Graph Cut
GrabCut
Image Stitching
Image Super-Resolution
Photo Collage
Video Collage
Video Tapestry
Video Creativity
Video Highlights
Video Summarization
Face Detection
VR
SLAM
OCR
Papers
Applications
Projects
Resources
Libraries
Datasets
Blogs
Conferences
Resources

Courses

Mobile Computer Vision (Spring 2015)

homepage: http://web.stanford.edu/class/cs231m/
syllabus: http://web.stanford.edu/class/cs231m/syllabus.html
projects: http://web.stanford.edu/class/cs231m/projects.html
resources: http://web.stanford.edu/class/cs231m/resources.html

CSCI1950-G Computational Photography

http://cs.brown.edu/courses/csci1950-g/

MIT CSAIL: 6.819/6.869: Advances in Computer Vision (Fall 2015)

homepage: http://6.869.csail.mit.edu/fa15/index.html

EECS 432 Advanced Computer Vision

course website: http://www.ece.northwestern.edu/~yingwu/teaching/EECS432/index.htmlc
handouts:http://www.ece.northwestern.edu/~yingwu/teaching/EECS432/EECS432_hand.html

EECS 286 Advanced Topics in Computer Vision

homepage: http://faculty.ucmerced.edu/mhyang/course/eecs286/index.htm
syllabus: http://faculty.ucmerced.edu/mhyang/course/eecs286/syllabus.htm
lectures: http://faculty.ucmerced.edu/mhyang/course/eecs286/lecture.htm
lecture(“How to get your CVPR paper rejected?”):http://faculty.ucmerced.edu/mhyang/course/eecs286/lectures/introduction.pptx

CS280: Computer Vision (University of California Berkeley)

homepage: http://www-inst.eecs.berkeley.edu/~cs280/sp15/index.html
lectures: http://docs.huihoo.com/computer-vision/berkeley/cs280-computer-vision/

CSCI2951-T Data-driven Computer Vision (Spring 2016)

instructor: Genevieve Patterson
homepage: http://cs.brown.edu/courses/csci2951-t/

Edge detection

Image-feature-detection-using-Phase-Stretch-Transform

github: https://github.com/JalaliLabUCLA/Image-feature-detection-using-Phase-Stretch-Transform
wikipedia: https://en.wikipedia.org/wiki/Phase_stretch_transform

Images Denoising

Fast Burst Images Denoising(SIGGRAPH Asia 2014. CUHK, Microsoft Research)

project: http://personal.ie.cuhk.edu.hk/~lz013/projects/BurstDenoising.html
paper: http://personal.ie.cuhk.edu.hk/~lz013/papers/burstdenoising.pdf

Robust non-linear regression analysis: A greedy approach employing kernels and application to image denoising (KGARD)

arxiv: http://arxiv.org/abs/1601.00595
code(Matlab): http://bouboulis.mysch.gr/kernels.html

Blind Image Denoising via Dependent Dirichlet Process Tree

arxiv: http://arxiv.org/abs/1601.03117

Deblur

Good Regions to Deblur

project page: https://eng.ucmerced.edu/people/zhu/GoodRegion.html
paper: https://eng.ucmerced.edu/people/zhu/ECCV12.pdf
code(Matlab): https://eng.ucmerced.edu/people/zhu/ECCV12_code.zip

Painting

Real-Time Gradient-Domain Painting (SIGGRAPH 2009)

homepage: http://graphics.cs.cmu.edu/projects/gradient-paint/
paper: http://graphics.cs.cmu.edu/projects/gradient-paint/grad.light.r2226.pdf

Combining Sketch and Tone for Pencil Drawing Production (NPAR 2012 Best Paper Award)

homepage: http://www.cse.cuhk.edu.hk/~leojia/projects/pencilsketch/pencil_drawing.htm
paper: http://www.cse.cuhk.edu.hk/~leojia/projects/pencilsketch/npar12_pencil.pdf
github: https://github.com/fumin/pencil

RGB-W: When Vision Meets Wireless

paper: http://vision.stanford.edu/pdf/RGBW_ICCV15.pdf

Computer Vision Datasets

website: http://clickdamage.com/sourcecode/index.html
code: http://clickdamage.com/sourcecode/cv_datasets.php
BaiduPan: http://pan.baidu.com/s/1pJmqD4n

A Computational Approach for Obstruction-Free Photography

paper:https://people.csail.mit.edu/mrub/papers/ObstructionFreePhotograpy_SIGGRAPH2015.pdf

My Text in Your Handwriting

homepage: http://visual.cs.ucl.ac.uk/pubs/handwriting/
paper: http://visual.cs.ucl.ac.uk/pubs/handwriting/handwriting_visual_main.pdf

Bag Of Words

Activity Recognition

Latent Hierarchical Model for Activity Recognition

paper: http://arxiv.org/abs/1503.01820
github: https://github.com/louxi11/activity_recognition
author page: https://staff.fnwi.uva.nl/n.hu/

License Plate Recognition

website: http://www.openalpr.com/
github: https://github.com/openalpr/openalpr
tech reciew: http://arstechnica.com/business/2015/12/new-open-source-license-plate-reader-software-lets-you-make-your-own-hot-list/

Reading Car License Plates Using Deep Convolutional Neural Networks and LSTMs

arxiv: http://arxiv.org/abs/1601.05610

Image Retrieval

Multi-modal image retrieval with random walk on multi-layer graphs

arxiv: http://arxiv.org/abs/1607.03406

Image Summary

Summarizing Visual Data Using Bidirectional Similarity

homepage:http://denis.simakov.info/weizmann/summarization_talk_20101116/summarization.html
paper:http://www.wisdom.weizmann.ac.il/~vision/VisualSummary/bidirectional_similarity_CVPR2008.pdf

Image Retargeting/Editing

PatchMatch: A Randomized Correspondence Algorithm for Structural Image Editing

homepage(paper+code): http://gfx.cs.princeton.edu/pubs/Barnes_2009_PAR/
paper: http://gfx.cs.princeton.edu/pubs/Barnes_2009_PAR/patchmatch.pdf
code: http://gfx.cs.princeton.edu/pubs/Barnes_2009_PAR/patchmatch-2.1.zip

The Generalized PatchMatch Correspondence Algorithm

homapage(paper+code): http://gfx.cs.princeton.edu/pubs/Barnes_2010_TGP/index.php
paper: http://gfx.cs.princeton.edu/pubs/Barnes_2010_TGP/generalized_pm.pdf
code: http://www.cs.princeton.edu/gfx/pubs/Barnes_2009_PAR/patchmatch-2.0.zip

Image Editing

Seamless Image Editing

homepage: http://www.cmlab.csie.ntu.edu.tw/~dreamway/seamless/

Image Inpaiting

Patch-based Texture Synthesis for Image Inpainting

arxiv: http://arxiv.org/abs/1605.01576

Image Dithering

Image Dithering: Eleven Algorithms and Source Code

blog: http://www.tannerhelland.com/4660/dithering-eleven-algorithms-source-code/

Image Enhancement

LIME: A Method for Low-light IMage Enhancement

arxiv: http://arxiv.org/abs/1605.05034
github: http://cs.tju.edu.cn/orgs/vision/~xguo/code/LIME.zip
author homepage: http://cs.tju.edu.cn/orgs/vision/~xguo/homepage.htm

SelPh: Progressive Learning and Support of Manual Photo Color Enhancement

homepage: http://koyama.xyz/project/SelPh/
paper: http://koyama.xyz/project/SelPh/chi2016_paper.pdf
bitbucket: https://bitbucket.org/yukikoyama/selph/

Image Resizing

blog: http://parellagram.com/posts/carving
github: https://github.com/aaparella/carve

Image Cloning

Coordinates for Instant Image Cloning (SIGGRAPH 2009)

homepage: http://www.cs.huji.ac.il/~danix/mvclone/
paper: http://www.cs.huji.ac.il/~danix/mvclone/files/mvc-final-opt.pdf

Image Compositing

Interactive Digital Photomontage (SIGGRAPH 2004)

homepage: http://grail.cs.washington.edu/projects/photomontage/
code: http://grail.cs.washington.edu/projects/photomontage/release/
paper: http://grail.cs.washington.edu/projects/photomontage/photomontage.pdf
paper:http://www.researchgate.net/publication/2941744_Interactive_Digital_Photomontage

Panorama Stitching

CS510 Visual Computing, Project 2: Panorama Stitching

http://web.cecs.pdx.edu/~kstew2/cs510vision/stitcher/

Image Stylization

stylize: Regressor based image stylization

github: https://github.com/Newmu/stylize

Image Haze Removal

Single Image Haze Removal

project page: http://research.microsoft.com/en-us/um/people/kahe/cvpr09/

DehazeNet: An End-to-End System for Single Image Haze Removal

arxiv: http://arxiv.org/abs/1601.07661

Graph Cut

GrabCut

“GrabCut” — Interactive Foreground Extraction using Iterated Graph Cuts

paper: http://cvg.ethz.ch/teaching/cvl/2012/grabcut-siggraph04.pdf

OpenCV 3.1: Interactive Foreground Extraction using GrabCut Algorithm

http://docs.opencv.org/master/d8/d83/tutorial_py_grabcut.html#gsc.tab=0

Image Stitching

Natural and Seamless Image Composition with Color Control

http://www3.ntu.edu.sg/home/asjfcai/tip04594.pdf

Object-aware Gradient-Domain Image Compositing

http://www.cg.cs.tu-bs.de/media/publications/Eisemann11OAG.pdf

Improving Image Matting using Comprehensive Sampling Sets

http://www.cv-foundation.org/openaccess/content_cvpr_2013/papers/Shahrian_Improving_Image_Matting_2013_CVPR_paper.pdf

Multi-scale Image Harmonization

homepage: http://gvi.seas.harvard.edu/paper/multiscale-image-harmonization
paper: http://gvi.seas.harvard.edu/sites/all/files/Harmonization_SIGGRAPH10.pdf
slides: http://gvi.seas.harvard.edu/sites/all/files/Harmonization_SIGGRAPH10.pptx

Drag-and-Drop Pasting

http://research.microsoft.com/pubs/69331/dragdroppasting_siggraph06.pdf

Cross Dissolve Without Cross Fade: Preserving Contrast, Color and Salience in Image Compositing

https://www.cl.cam.ac.uk/research/rainbow/projects/compositing/EG06-Cross-Dissolve-Without-Cross-Fade.pdf

Snap Image Composition

http://www.cs.huji.ac.il/~peleg/papers/SnapComposition.pdf

Stitching Stabilizer: Two-frame-stitching Video Stabilization for Embedded Systems

arxiv: http://arxiv.org/abs/1603.06678

Stitching and Matting

lectures: http://web.cs.hacettepe.edu.tr/~aykut/classes/spring2015/bil721/lectures/w06-stitching-matting.pdf

Image Stitching

lectures: https://courses.engr.illinois.edu/cs498dwh/fa2010/lectures/Lecture%2017%20-%20Photo%20Stitching.pdf

Graphics isn’t all about 3-D

lectures: http://www.cs.cmu.edu/afs/cs/academic/class/15462-s09/www/lec/25/lec25.pdf
slides: http://upcommons.upc.edu/bitstream/handle/2099.1/22861/PujolAlba-TFG-FinalReport.pdf;jsessionid=7AE46AE2A5420F75760F246381D429BC?sequence=5

Assignment: Image stitching with RANSAC

assignments: https://people.cs.umass.edu/~elm/Teaching/Docs/assign_RANSAC.pdf

OpenCV panorama stitching

blog: http://www.pyimagesearch.com/2016/01/11/opencv-panorama-stitching/

Real-time panorama and image stitching with OpenCV

blog: http://www.pyimagesearch.com/2016/01/25/real-time-panorama-and-image-stitching-with-opencv/

Image Super-Resolution

Super-Resolution From a Single Image

project: http://www.wisdom.weizmann.ac.il/~vision/SingleImageSR.html
paper:http://www.wisdom.weizmann.ac.il/~vision/single_image_SR/files/single_image_SR.pdf

Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging

paper: http://www.its.caltech.edu/~roarke/research/FPM/FPM_Aperture_Scanning.pdf
slides: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6754138

Single Image Super-Resolution from Transformed Self-Exemplars

homepage: https://sites.google.com/site/jbhuang0604/publications/struct_sr
github: https://github.com/jbhuang0604/SelfExSR

Photo Collage

AutoCollage (SIGGRAPH 2006)

intro: “Autocollage defines different energies to encourage the selection of a representative set of images, select particular object classes, and encourage a spatially efficient and seamless layout. The optimization is divided into a sequence of steps: from static ranking of images, through region of interest detection, optimal packing by the branch-and-bound algorithm, and lastly graph-cut alpha expansion. The core packing algorithm is limited; for example, user interaction cannot be integrated. The packing algorithm cannot deal with images with multiple salient regions which are assigned different weights. Further, the blending still may bring artifacts on the boundaries of different images.”
homepage: http://research.microsoft.com/en-us/projects/i3l/autocollage.aspx
paper:http://research.microsoft.com/pubs/67894/autocollage_rotheretal_siggraph2006.pdf
slides: http://research.microsoft.com/en-us/UM/cambridge/projects/VisionImageVideoEditing/autocollage/TalkSiggraph2006Compressed.zip
demo: http://research.microsoft.com/en-us/um/cambridge/projects/autocollage/

Picture Collage (2006)

paper: http://research.microsoft.com/en-us/um/people/jiansun/papers/PictureCollage_CVPR2006.pdf
paper: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.89.5727

Picture Collage (2009)

intro: “formulate the picture collage creation problem in a conditional random field model, which integrates image salience, canvas constraint, natural preference, and user interaction”
paper: http://mmlab.ie.cuhk.edu.hk/archive/2009/07_Picture.pdf

Efficient Optimization of Photo Collage

paper: http://research.microsoft.com/pubs/80783/Collage_techreport.pdf

Video Collage

Video collage: A novel presentation of video sequence (ICME 2007)

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.130.3728&rep=rep1&type=pdf

Stained-Glass Visualization for Highly Condensed Video Summaries (ICME 2004)

https://www.fxpal.com/publications/stained-glass-visualization-for-highly-condensed-video-summaries.pdf

Stained Glass Photo Collages

http://uist.acm.org/archive/adjunct/2004/pdf/posters/p7-girgensohn.pdf

Visual Storylines: Semantic Visualization of Movie Sequence

paper: http://cg.cs.tsinghua.edu.cn/papers/C&G2012_videostoryline.pdf
paper: http://cg.cs.tsinghua.edu.cn/people/~taochen/papers/VisualStorylines.pdf

Video collage: presenting a video sequence using a single image

http://iris.usc.edu/people/yangbo/papers/vcj08.pdf

Efficient Optimization of Photo Collage

http://research.microsoft.com/en-us/people/yichenw/collage_techreport.pdf

Puzzle-like Collage (2010)

http://webee.technion.ac.il/~ayellet/Ps/10-PuzzleCollage.pdf

Browsing Large Image Datasets through Voronoi Diagrams

http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=576998825C3E40A32826A00B64089DF6?doi=10.1.1.230.5997&rep=rep1&type=pdf

Content-aware Photo Collage Using Circle Packing (NJU. TVCG 2014)

homepage: http://cs.nju.edu.cn/ywguo/PhotoCollage/Index.html
paper: http://cs.nju.edu.cn/ywguo/webs/paperdownload/Content-aware%20Photo%20Collage%20Using%20Circle%20Packing.pdf
demo: http://cs.nju.edu.cn/ywguo/PhotoCollage/dload.html

Automatic Generation of Social Media Snippets for Mobile Browsing (Microsoft Research. ACM Multimedia 2013)

homepage: http://research.microsoft.com/apps/pubs/default.aspx?id=204877
paper: http://research.microsoft.com/pubs/204877/mm035-yin.pdf

Video Tapestry

Digital Tapestry (MSR. CVPR 2005)

intro: “formulates the selection of salient regions and their placement together as a Markov random field (MRF) problem. Each image is represented as a set of blocks, and the multiple-class labeling problem with non-metric constraints is optimized by “truncating” the non-regular energy. However, artifacts are also introduced along the boundaries of neighboring salient regions coming from two different images in digital tapestry, although some artifact removal methods can be used”
homepage: http://research.microsoft.com/apps/pubs/default.aspx?id=67404
paper: http://pub.ist.ac.at/~vnk/papers/tapestry_cvpr05.pdf

Video Tapestries with Continuous Temporal Zoom (Princeton. SIGGRAPH 2010)

homepage: http://gfx.cs.princeton.edu/gfx/pubs/Barnes_2010_VTW/index.php
paper: http://www.connellybarnes.com/work/publications/2010_tapestry_electronic.pdf

Video Creativity

6 Seconds of Sound and Vision: Creativity in Micro-Videos (CVPR 2014)

homepage: http://www.di.unito.it/~schifane/dataset/vine-dataset-cvpr14/
arxiv: http://arxiv.org/abs/1411.4080

Video Highlights

Ranking Domain-specific Highlights by Analyzing Edited Videos (ECCV 2014)

intro: use a dataset obtained by crawling Youtube data. find pairs of raw and edited videos, used in training, by matching all pairs of videos within a certain category(e.g. gymnastics). The size of their dataset is, however, limited by the availability of domain-specific videos in both raw and edited forms.
homepage: http://aliensunmin.github.io/project/at-a-glance/
paper: http://grail.cs.washington.edu/wp-content/uploads/2015/08/sun2014rdh.pdf
paper: https://drive.google.com/file/d/0ByJgUdTb1N2CM3Y5VU1BRjlmR3c/edit
tech: https://drive.google.com/file/d/0ByJgUdTb1N2CM1ktb1N4RVV3Mzg/view
github: https://github.com/aliensunmin/DomainSpecificHighlight

Salient Montages from Unconstrained Videos

homepage: http://aliensunmin.github.io/project/at-a-glance/
paper: http://grail.cs.washington.edu/wp-content/uploads/2015/08/sun2014smf.pdf
paper: https://drive.google.com/file/d/0ByJgUdTb1N2CbzNYTjdxX0ZiRmc/edit
github: https://github.com/aliensunmin/salientMontages

Video Summarization

Creating Summaries from User Videos (ECCV 2014)

project page: https://people.ee.ethz.ch/~gyglim/vsum/index.php
paper: https://people.ee.ethz.ch/~gyglim/vsum/GygliECCV14_vsum.pdf
paper:http://www.vision.ee.ethz.ch/~hegrabne/papers/Gygli2014CreatingSummariesfrom.pdf
code: https://people.ee.ethz.ch/~gyglim/vsum/index.php#sf_code

Joint Summarization of Large-scale Collections of Web Images and Videos for Storyline Reconstruction

intro: CVPR 2014
paper: http://www.cs.cmu.edu/~gunhee/publish/cvpr14_videostory.pdf

Video Summarization by Learning Submodular Mixtures of Objectives (CVPR 2015)

paper: http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Gygli_Video_Summarization_by_2015_CVPR_paper.pdf

TVSum: Summarizing Web Videos Using Titles

paper: http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Song_TVSum_Summarizing_Web_2015_CVPR_paper.pdf

Summarizing While Recording: Context-Based Highlight Detection for Egocentric Videos

keywords: structured SVM (SSVM)
paper: http://www.umiacs.umd.edu/~morariu/publications/LinEgocentricICCVW15.pdf

Face Detection

Build a Face Detection App Using Node.js and OpenCV

http://www.sitepoint.com/face-detection-nodejs-opencv/

FaceTracker: Real time deformable face tracking in C++ with OpenCV 2

github: https://github.com/kylemcdonald/FaceTracker

A Fast and Accurate Unconstrained Face Detector

homepage: http://www.cbsr.ia.ac.cn/users/scliao/projects/npdface/index.html
github: https://github.com/CitrusRokid/OpenNPD

libfacedetection: A binary library for face detection in images. You can use it free of charge with any purpose

github: https://github.com/ShiqiYu/libfacedetection

jQuery Face Detection Plugin: A jQuery plugin to detect faces on images, videos and canvases

website: http://facedetection.jaysalvat.com/
github: https://github.com/jaysalvat/jquery.facedetection

VR

Surround360 System: Facebook’s open source hardware and software for capturing stereoscopic 3D 360 video for VR

homepage: https://facebook360.fb.com/facebook-surround-360/
code: https://code.facebook.com/posts/265413023819735/surround-360-is-now-open-source/
github: https://github.com/facebook/Surround360

SLAM

Why SLAM Matters, The Future of Real-Time SLAM, and Deep Learning vs SLAM

blog: http://www.computervisionblog.com/2016/01/why-slam-matters-future-of-real-time.html?m=1

一起做RGB-D SLAM

blog:http://www.cnblogs.com/gaoxiang12/tag/%E4%B8%80%E8%B5%B7%E5%81%9ARGB-D%20SLAM/
github: https://github.com/gaoxiang12/rgbd-slam-tutorial-gx

PySceneDetect: a command-line application and a Python library for automatically detecting scene changes in video files

homepage: http://pyscenedetect.readthedocs.org/en/latest/

The Future of Real-Time SLAM and Deep Learning vs SLAM

blog: http://www.computervisionblog.com/2016/01/why-slam-matters-future-of-real-time.html

Awesome SLAM

github: https://github.com/kanster/awesome-slam

ORB-SLAM2: Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

github: https://github.com/raulmur/ORB_SLAM2

OCR

Ocular: a state-of-the-art historical OCR system

github: https://github.com/tberg12/ocular

【OCR/机器学习/搜索引擎】基于 Tesseract的图文识别搜

github: https://github.com/daijiale/OCR_FontsSearchEngine

Papers

Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects

arxiv: http://arxiv.org/abs/1602.00753
project page: http://grail.cs.washington.edu/projects/size/

Atoms of recognition in human and computer vision

homepage: http://www.wisdom.weizmann.ac.il/~dannyh/Mircs/mircs.html
paper: https://s3-us-west-1.amazonaws.com/disneyresearch/wp-content/uploads/20150929153916/Live-Texturing-of-Augmented-Reality-Characters-from-Colored-Drawings-Paper.pdf

Live Texturing of Augmented Reality Characters from Colored Drawings

homepage: https://www.disneyresearch.com/publication/live-texturing-of-augmented-reality-characters/

Colorization for Image Compression

arxiv: http://arxiv.org/abs/1606.06314

Face2Face: Real-time Face Capture and Reenactment of RGB Videos

project page: http://www.graphics.stanford.edu/~niessner/thies2016face.html
paper:http://www.graphics.stanford.edu/~niessner/papers/2016/1facetoface/thies2016face.pdf

Applications

Target acquired: Finding targets in drone and quadcopter video streams using Python and OpenCV

http://www.pyimagesearch.com/2015/05/04/target-acquired-finding-targets-in-drone-and-quadcopter-video-streams-using-python-and-opencv/

FaceDirector: Continuous Control of Facial Performance in Video

homepage: http://www.disneyresearch.com/publication/facedirector/
paper: http://disneyresearch.s3-us-west-1.amazonaws.com/wp-content/uploads/20151210174750/FaceDirector-Continuous-Control-of-Facial-Performance-in-Video-Paper.pdf

Real-time Expression Transfer for Facial Reenactment

homepage: http://graphics.stanford.edu/~niessner/thies2015realtime.html
paper: http://graphics.stanford.edu/~niessner/papers/2015/10face/thies2015realtime.pdf

Photo Stylistic Brush: Robust Style Transfer via Superpixel-Based Bipartite Graph

arxiv: http://arxiv.org/abs/1606.03871

Projects

OpenBR: Open Source Biometrics, Face Recognition, Age Estimation, Gender Estimation

homepage: http://openbiometrics.org/
github: https://github.com/biometrics/openbr
docs: http://openbiometrics.org/docs/index.html

SmartMirror

github: https://github.com/Shinao/SmartMirror

Resources

Awesome Computer Vision

github: https://github.com/jbhuang0604/awesome-computer-vision

Resources: Visual Recognition and Search

intro: “Non-exhaustive list of state-of-the-art implementations related to visual recognition and search”
blog: http://rogerioferis.com/VisualRecognitionAndSearch2014/Resources.html

Libraries

BoofCV: an open source Java library for real-time computer vision and robotics applications

http://boofcv.org/index.php?title=Main_Page

tracking.js: A modern approach for Computer Vision on the web

homepage: https://trackingjs.com/
github: https://github.com/eduardolundgren/tracking.js/

FastCV Computer Vision SDK

homepage: https://developer.qualcomm.com/software/fastcv-sdk

Video++, a C++14 high performance video and image processing library

github: https://github.com/matt-42/vpp
doc: http://documentup.com/matt-42/vpp

VLFeat – Vision Lab Features Library

intro: Algorithms include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others
homapage: http://www.vlfeat.org/
github: https://github.com/vlfeat/vlfeat

Datasets

CVonline: Image Databases

http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm

Yet Another Computer Vision Index To Datasets (YACVID)

http://riemenschneider.hayko.at/vision/dataset/

Blogs

From feature descriptors to deep learning: 20 years of computer vision

blog: http://www.computervisionblog.com/2015/01/from-feature-descriptors-to-deep.html

**Unsupervised Computer Vision: The State of the ArtStitch Fix Technology – Multithreaded**

blog: http://multithreaded.stitchfix.com/blog/2016/02/04/computer-vision-state-of-the-art
slides: http://pan.baidu.com/s/1c0Sxzvq

Exploring Computer Vision

Part I: Convolutional Neural Networks: https://indico.io/blog/exploring-computer-vision-convolutional-neural-nets/
Part II: Transfer Learning: https://indico.io/blog/exploring-computer-vision-transfer-learning/

Conferences

SIGGRAPH 2016 papers on the web

http://kesen.realtimerendering.com/sig2016.html

Resources

The Ultimate List of 300+ Computer Vision Resources

blog: https://hackerlists.com/computer-vision-resources/

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Computer Vision Resources