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 Awesome Computer Vision: !Awesome (https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg) (https://github.com/sindresorhus/awesome)
 Awesome Computer Vision: !Awesome (https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg) (https://github.com/sindresorhus/awesome)
A curated list of awesome computer vision resources, inspired by awesome-php (https://github.com/ziadoz/awesome-php).
For a list people in computer vision listed with their academic genealogy, please visit here (https://github.com/jbhuang0604/awesome-computer-vision/blob/master/people.md)
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⟡ Vision Science: Photons to Phenomenology (http://www.amazon.com/Vision-Science-Phenomenology-Stephen-Palmer/dp/0262161834/) - Stephen E. Palmer 1999
⟡ Visual Object Recognition synthesis lecture (http://www.morganclaypool.com/doi/abs/10.2200/S00332ED1V01Y201103AIM011) - Kristen Grauman and Bastian Leibe 2011
⟡ Computer Vision for Visual Effects (http://cvfxbook.com/) - Richard J. Radke, 2012
⟡ High dynamic range imaging: acquisition, display, and image-based lighting
 (http://www.amazon.com/High-Dynamic-Range-Imaging-Second/dp/012374914X) - Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., Myszkowski, K 2010
⟡ High dynamic range imaging: acquisition, display, and image-based lighting (http://www.amazon.com/High-Dynamic-Range-Imaging-Second/dp/012374914X) - Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., Myszkowski, K 2010
⟡ Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics (https://people.csail.mit.edu/jsolomon/share/book/numerical_book.pdf) - Justin Solomon 2015
⟡ Image Processing and Analysis (https://www.amazon.com/Processing-Analysis-Activate-Learning-Engineering/dp/1285179528) - Stan Birchfield 2018
⟡ Computer Vision, From 3D Reconstruction to Recognition (http://web.stanford.edu/class/cs231a/) - Silvio Savarese 2018
@@ -99,8 +98,8 @@
OpenCV Programming
⟡ Learning OpenCV: Computer Vision with the OpenCV Library (http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134) - Gary Bradski and Adrian Kaehler
⟡ Practical Python and OpenCV (https://www.pyimagesearch.com/practical-python-opencv/) - Adrian Rosebrock
⟡ OpenCV Essentials (http://www.amazon.com/OpenCV-Essentials-Oscar-Deniz-Suarez/dp/1783984244/ref=sr_1_1?s=books&ie=UTF8&qid=1424594237&sr=1-1&keywords=opencv+essentials#) - Oscar Deniz Suarez, Mª del Milagro 
Fernandez Carrobles, Noelia Vallez Enano, Gloria Bueno Garcia, Ismael Serrano Gracia
⟡ OpenCV Essentials (http://www.amazon.com/OpenCV-Essentials-Oscar-Deniz-Suarez/dp/1783984244/ref=sr_1_1?s=books&ie=UTF8&qid=1424594237&sr=1-1&keywords=opencv+essentials#) - Oscar Deniz Suarez, Mª del Milagro Fernandez Carrobles, Noelia
Vallez Enano, Gloria Bueno Garcia, Ismael Serrano Gracia
Machine Learning
⟡ Pattern Recognition and Machine Learning (http://research.microsoft.com/en-us/um/people/cmbishop/prml/index.htm) - Christopher M. Bishop 2007
@@ -114,8 +113,7 @@
⟡ Bayesian Reasoning and Machine Learning (http://www.cs.ucl.ac.uk/staff/d.barber/brml/) - David Barber, Cambridge University Press, 2012
Fundamentals
 ⟡ Linear Algebra and Its Applications
 (http://www.amazon.com/Linear-Algebra-Its-Applications-4th/dp/0030105676/ref=sr_1_4?ie=UTF8&qid=1421433773&sr=8-4&keywords=Linear+Algebra+and+Its+Applications) - Gilbert Strang 1995
 ⟡ Linear Algebra and Its Applications (http://www.amazon.com/Linear-Algebra-Its-Applications-4th/dp/0030105676/ref=sr_1_4?ie=UTF8&qid=1421433773&sr=8-4&keywords=Linear+Algebra+and+Its+Applications) - Gilbert Strang 1995
Courses
@@ -370,8 +368,7 @@
 ⟡ Multi-frame image super-resolution (http://www.robots.ox.ac.uk/~vgg/software/SR/)
* Pickup, L. C. Machine Learning in Multi-frame Image Super-resolution, PhD thesis 2008
 ⟡ Markov Random Fields for Super-Resolution (http://people.csail.mit.edu/billf/project%20pages/sresCode/Markov%20Random%20Fields%20for%20Super-Resolution.html)
* W. T Freeman and C. Liu. Markov Random Fields for Super-resolution and Texture Synthesis. In A. Blake, P. Kohli, and C. Rother, eds., Advances in Markov Random Fields for Vision and Image Processing, Chapter 1 
0. MIT Press, 2011 
* W. T Freeman and C. Liu. Markov Random Fields for Super-resolution and Texture Synthesis. In A. Blake, P. Kohli, and C. Rother, eds., Advances in Markov Random Fields for Vision and Image Processing, Chapter 10. MIT Press, 2011
 ⟡ Sparse regression and natural image prior (https://people.mpi-inf.mpg.de/~kkim/supres/supres.htm)
* K. I. Kim and Y. Kwon, "Single-image super-resolution using sparse regression and natural image prior", IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 32, no. 6, pp. 1127-1133, 2010.
 ⟡ Single-Image Super Resolution via a Statistical Model (http://www.cs.technion.ac.il/~elad/Various/SingleImageSR_TIP14_Box.zip)
@@ -381,8 +378,8 @@
 ⟡ Patch-wise Sparse Recovery (http://www.ifp.illinois.edu/~jyang29/ScSR.htm)
* Jianchao Yang, John Wright, Thomas Huang, and Yi Ma. Image super-resolution via sparse representation. IEEE Transactions on Image Processing (TIP), vol. 19, issue 11, 2010.
 ⟡ Neighbor embedding (http://www.jdl.ac.cn/user/hchang/doc/code.rar)
* H. Chang, D.Y. Yeung, Y. Xiong. Super-resolution through neighbor embedding. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), vol.1, pp.275-282, Washington 
, DC, USA, 27 June - 2 July 2004. 
* H. Chang, D.Y. Yeung, Y. Xiong. Super-resolution through neighbor embedding. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), vol.1, pp.275-282, Washington, DC, USA, 27 June - 2 Ju 
ly 2004. 
 ⟡ Deformable Patches (https://sites.google.com/site/yuzhushome/single-image-super-resolution-using-deformable-patches)
* Yu Zhu, Yanning Zhang and Alan Yuille, Single Image Super-resolution using Deformable Patches, CVPR 2014
 ⟡ SRCNN (http://mmlab.ie.cuhk.edu.hk/projects/SRCNN.html)