Computer Vision Resources

• from: http://handong1587.github.io/computer_vision/2015/09/12/cv-resources.html
  Published: 12 Sep 2015 computer_vision

Jump to...

1. Courses
2. Edge detection
3. Images Denoising
4. Deblur
5. Painting
6. Bag Of Words
7. Activity Recognition
8. License Plate Recognition
9. Image Retrieval
10. Image Summary
11. Image Retargeting/Editing
12. Image Editing
13. Image Inpaiting
14. Image Dithering
15. Image Enhancement
16. Image Resizing
17. Image Cloning
18. Image Compositing
19. Image Stylization
20. Image Haze Removal
21. Graph Cut
22. GrabCut
23. Image Stitching
24. Image Super-Resolution
25. Photo Collage
26. Video Collage
27. Video Tapestry
28. Video Creativity
29. Video Highlights
30. Video Summarization
31. Face Detection
32. VR
33. SLAM
34. OCR
35. Papers
36. Applications
37. Projects
38. Resources
39. Libraries
40. Datasets
41. Blogs
42. Conferences
43. 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:
• 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 Art

Stitch 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/

                ---------------^-^--------------------保证不让你失望----------------------------------*-*----

更多详细内容请关注公众号：目标检测和深度学习

--------------*-*---------------------------------------------------------------------------------*-*----