Awesome List Updates on Jan 18, 2015
3 awesome lists updated today.
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1. Awesome Gametalks
GDC Talks / Table of Contents
- [2012] Creating a Sequel to a Game That Doesn't Need One: Chet Faliszek, Erik Wolpaw (Valve)
2. Awesome Bigdata
Data Visualization
- D3Plus - A fairly robust set of reusable charts and styles for d3.js.
3. Awesome Computer Vision
Computer Vision
- Vision Science: Photons to Phenomenology - Stephen E. Palmer 1999
- Visual Object Recognition synthesis lecture - Kristen Grauman and Bastian Leibe 2011
- The Three R's of Computer Vision - Jitendra Malik (UC Berkeley) 2013
- Applications to Machine Vision - Andrew Blake (Microsoft Research) 2008
Machine Learning and Statistical Learning
- Learning from Data - Yaser S. Abu-Mostafa (Caltech)
- Statistical Learning - Trevor Hastie and Rob Tibshirani (Stanford University)
- Statistical Learning Theory and Applications - Tomaso Poggio, Lorenzo Rosasco, Carlo Ciliberto, Charlie Frogner, Georgios Evangelopoulos, Ben Deen (MIT)
- Statistical Learning - Genevera Allen (Rice University)
- Practical Machine Learning - Michael Jordan (UC Berkeley)
Optimization
- Optimization at MIT - (MIT)
- Convex Optimization - Ryan Tibshirani (CMU)
- Optimization Algorithms in Machine Learning - Stephen J. Wright (University of Wisconsin-Madison)
- Convex Optimization - Lieven Vandenberghe (University of California, Los Angeles)
Conference papers on the web
- CVPapers - Computer vision papers on the web
- SIGGRAPH Paper on the web - Graphics papers on the web
- NIPS Proceedings - NIPS papers on the web
3D Computer Vision
- 3D Computer Vision: Past, Present, and Future - Steve Seitz (University of Washington) 2011
Internet Vision
- The Distributed Camera - Noah Snavely (Cornell University) 2011
- Planet-Scale Visual Understanding - Noah Snavely (Cornell University) 2014
- A Trillion Photos - Steve Seitz (University of Washington) 2013
Computational Photography
- Reflections on Image-Based Modeling and Rendering - Richard Szeliski (Microsoft Research) 2013
- Photographing Events over Time - William T. Freeman (MIT) 2011
- Old and New algorithm for Blind Deconvolution - Yair Weiss (The Hebrew University of Jerusalem) 2011
- A Tour of Modern "Image Processing" - Peyman Milanfar (UC Santa Cruz/Google) 2010
- Topics in image and video processing Andrew Blake (Microsoft Research) 2007
- Computational Photography - William T. Freeman (MIT) 2012
Learning and Vision
- Where machine vision needs help from machine learning - William T. Freeman (MIT) 2011
- Learning in Computer Vision - Simon Lucey (CMU) 2008
- Learning and Inference in Low-Level Vision - Yair Weiss (The Hebrew University of Jerusalem) 2009
Object Recognition
- Generative Models for Visual Objects and Object Recognition via Bayesian Inference - Fei-Fei Li (Stanford University)
Graphical Models
- Graphical Models for Computer Vision - Pedro Felzenszwalb (Brown University) 2012
- Graphical Models - Zoubin Ghahramani (University of Cambridge) 2009
- Machine Learning, Probability and Graphical Models - Sam Roweis (NYU) 2006
- Graphical Models and Applications - Yair Weiss (The Hebrew University of Jerusalem) 2009
Machine Learning
- Introduction To Bayesian Inference - Christopher Bishop (Microsoft Research) 2009
- Support Vector Machines - Chih-Jen Lin (National Taiwan University) 2006
Deep Learning
- A tutorial on Deep Learning - Geoffrey E. Hinton (University of Toronto)
- Deep Learning - Ruslan Salakhutdinov (University of Toronto)
- Scaling up Deep Learning - Yoshua Bengio (University of Montreal)
- ImageNet Classification with Deep Convolutional Neural Networks - Alex Krizhevsky (University of Toronto)
- The Unreasonable Effectivness Of Deep Learning Yann LeCun (NYU/Facebook Research) 2014
Feature Detection and Extraction
Low-level Vision / Image Completion
Low-level Vision / Alpha Matting
Low-level Vision / Edge-preserving image processing
Contour Detection and Image Segmentation / Edge-preserving image processing
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