Awesome List Updates on Jan 19, 2015

4 awesome lists updated today.

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1. Awesome Perl

Args

• Data::Validator - Rule based validator on type constraint system.

• Smart::Args

Benchmarks / DSP

• Benchmark

• Dumbbench

• Parallel::Benchmark - Benchmark in multiprocesses

CLI / DSP

• App::Cmd - Write command line apps with less suffering.

• Getopt::Long - Extended processing of command line options.

Data Format / DSP

• Data::Dumper::Simple - Reduce and faster Data::Dumper and eval() equivalent

• Data::MessagePack

• JSON::PP

• JSON::XS

• Sereal

• Storable

• Text::Markdown

• TOML

• XML::LibXML

• YAML

Database Drivers / Relational Databases

• DBD::Pg - PostgreSQL driver for DBI.

• DBD::SQLite

Database Drivers / NoSQL Databases

• Cache::Memcached::Fast

• Mango - Pure-Perl non-blocking I/O MongoDB driver

• Redis

• Redis::Fast - Perl wrapper around hiredis driver

• UnQLite

Exception Handling / NoSQL Databases

• TryCatch - first class try catch semantics for Perl, without source filters

Form Frameworks / NoSQL Databases

• WWW::Form - Simple and extendable module that allows developers to handle HTML form input validation and display flexibly and consistently.

Module Development / NoSQL Databases

• Dist::Zilla - http://dzil.org/

Queueing / NoSQL Databases

• Gearman

• Qudo

• TheSchwartz

REST Frameworks / NoSQL Databases

• Dancer::Plugin::REST - A plugin for writing RESTful apps with Dancer

Testing / Testing Frameworks

• Test::Base - A Data Driven Testing Framework

• Test::Base::Less - Limited version of Test::Base

• Test::BDD::Cucumber - Implementation of the popular Cucumber framework in Perl

• Test::Class - Class-based testing. Support "setup" and "teardown".

• Test::Deep - Test deep and complex data structures with great flexibility.

• Test::Deep::Matcher

• Test::Kantan - simple, flexible, fun "Testing framework"

• Test::More

Testing / Test Double

• Test::Exception

• Test::Fatal - Simple module for verifying exceptions.

• Test::Mock::Guard - Mocking package subroutines.

• Test::MockTime

• Test::mysqld

• Test::TCP - Launch temporary TCP Server

• Test::Time - Simple module for faking system time.

Testing / Coverage

• Devel::Cover

• Devel::Cover::Report::Coveralls Report to Coveralls

Tools / Coverage

• Daiku - Make for Perl.

• Riji - Static site generator using markdown and git mainly for blogging.

2. Awesome Nodejs

Packages / Command-line utilities

• cfonts (⭐1.6k) - Sexy ASCII fonts for the console.

3. Awesome Gametalks

GDC Talks / Table of Contents

• [2012] How I Got My Mom to Play Through Plants vs. Zombies: George Fan (PopCap)

Other Talks / TED Talks

• [2013, IGDA Seattle] Game Design Tools (I Wish I learned About Sooner): Daniel Cook (Spry Fox)

• [2012, G.A.N.G Summit] Music Design in Games: Rich Vreeland (Disasterpeace)

• [2012, George Mason University] Lecture Series: Todd Howard (Bethesda)

4. Awesome Computer Vision

Fundamentals

• Linear Algebra and Its Applications - Gilbert Strang 1995

Conference papers on the web

• Calendar of Computer Image Analysis, Computer Vision Conferences - (USC)

Survey Papers

• Visionbib Survey Paper List

• Foundations and Trends® in Computer Graphics and Vision

• Computer Vision: A Reference Guide

Computer Vision

• The Future of Image Search - Jitendra Malik (UC Berkeley) 2008

• Should I do a PhD in Computer Vision? - Fatih Porikli (Australian National University)

3D Computer Vision

• Reconstructing the World from Photos on the Internet - Steve Seitz (University of Washington) 2013

Machine Learning

• Bayesian or Frequentist, Which Are You? - Michael I. Jordan (UC Berkeley)

Optimization

• Continuous Optimization in Computer Vision - Andrew Fitzgibbon (Microsoft Research)

• Beyond stochastic gradient descent for large-scale machine learning - Francis Bach (INRIA)

Deep Learning

• Deep Learning for Computer Vision - Rob Fergus (NYU/Facebook Research)

• High-dimensional learning with deep network contractions - Stéphane Mallat (Ecole Normale Superieure)

External Resource Links

• Computer Vision Resources - Jia-Bin Huang (UIUC)

• Computer Vision Algorithm Implementations - CVPapers

• Source Code Collection for Reproducible Research - Xin Li (West Virginia University)

General Purpose Computer Vision Library

• Open CV

• Matlab Computer Vision System Toolbox

Multiple-view Computer Vision

• MATLAB Functions for Multiple View Geometry

Feature Detection and Extraction

• SIFT
  • David G. Lowe, "Distinctive image features from scale-invariant keypoints," International Journal of Computer Vision, 60, 2 (2004), pp. 91-110.

• BRISK
  • Stefan Leutenegger, Margarita Chli and Roland Siegwart, "BRISK: Binary Robust Invariant Scalable Keypoints", ICCV 2011

• SURF
  • Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool, "SURF: Speeded Up Robust Features", Computer Vision and Image Understanding (CVIU), Vol. 110, No. 3, pp. 346--359, 2008

• FREAK
  • A. Alahi, R. Ortiz, and P. Vandergheynst, "FREAK: Fast Retina Keypoint", CVPR 2012

• AKAZE
  • Pablo F. Alcantarilla, Adrien Bartoli and Andrew J. Davison, "KAZE Features", ECCV 2012

Low-level Vision / Stereo Vision

• Middlebury Stereo Vision

• The KITTI Vision Benchmark Suite

• LIBELAS: Library for Efficient Large-scale Stereo Matching

• Ground Truth Stixel Dataset

Low-level Vision / Optical Flow

• Middlebury Optical Flow Evaluation

• MPI-Sintel Optical Flow Dataset and Evaluation

• The KITTI Vision Benchmark Suite

• HCI Challenge

• Coarse2Fine Optical Flow - Ce Liu (MIT)

Low-level Vision / Image Deblurring

• Spatially variant non-blind deconvolution

• Handling Outliers in Non-blind Image Deconvolution

• Hyper-Laplacian Priors

• From Learning Models of Natural Image Patches to Whole Image Restoration

• Deep Convolutional Neural Network for Image Deconvolution

• Neural Deconvolution

• Removing Camera Shake From A Single Photograph

• High-quality motion deblurring from a single image

• Two-Phase Kernel Estimation for Robust Motion Deblurring

• Blur kernel estimation using the radon transform

• Fast motion deblurring

• Blind Deconvolution Using a Normalized Sparsity Measure

• Blur-kernel estimation from spectral irregularities

• Efficient marginal likelihood optimization in blind deconvolution

• Unnatural L0 Sparse Representation for Natural Image Deblurring

• Edge-based Blur Kernel Estimation Using Patch Priors

• Blind Deblurring Using Internal Patch Recurrence

• Non-uniform Deblurring for Shaken Images

• Single Image Deblurring Using Motion Density Functions

• Image Deblurring using Inertial Measurement Sensors

• Fast Removal of Non-uniform Camera Shake

Low-level Vision / Alpha Matting

• Closed-form image matting

• Spectral Matting

• Learning-based Matting

• Improving Image Matting using Comprehensive Sampling Sets

Low-level Vision / Image Pyramid

• The Steerable Pyramid

• CurveLab

Contour Detection and Image Segmentation / Edge-preserving image processing

• Entropy Rate Superpixel

Interactive Image Segmentation / Edge-preserving image processing

• Random Walker

• Geodesic Segmentation

• Lazy Snapping

• Power Watershed

• Geodesic Graph Cut

• Segmentation by Transduction

Video Segmentation / Edge-preserving image processing

• Video Segmentation with Superpixels

• Efficient hierarchical graph-based video segmentation

• Object segmentation in video

Simultaneous localization and mapping / SLAM community:

• openSLAM

Simultaneous localization and mapping / Localization & Mapping:

• RatSLAM

Single-view Spatial Understanding / Localization & Mapping:

• Geometric Context - Derek Hoiem (CMU)

• Recovering Spatial Layout - Varsha Hedau (UIUC)

• Geometric Reasoning - David C. Lee (CMU)

• RGBD2Full3D (⭐23) - Ruiqi Guo (UIUC)

Object Detection / Localization & Mapping:

• Histograms of Sparse Codes for Object Detection

Nearest Neighbor Search / General purpose nearest neighbor search

• ANN: A Library for Approximate Nearest Neighbor Searching

• FLANN - Fast Library for Approximate Nearest Neighbors

• Fast k nearest neighbor search using GPU

Nearest Neighbor Search / Nearest Neighbor Field Estimation

• PatchMatch

• Generalized PatchMatch

• Coherency Sensitive Hashing

• PMBP: PatchMatch Belief Propagation (⭐27)

• TreeCANN

Visual Tracking / Image Super-resolutions

• Visual Tracker Benchmark

• Visual Tracker Benchmark v1.1

• VOT Challenge

• Princeton Tracking Benchmark

External Dataset Link Collection / Nearest Neighbor Field Estimation

• CV Datasets on the web - CVPapers

• Are we there yet? - Which paper provides the best results on standard dataset X?

• Computer Vision Dataset on the web

• Yet Another Computer Vision Index To Datasets

• ComputerVisionOnline Datasets

• CVOnline Dataset

• CV datasets

• visionbib

Low-level Vision / Image Super-resolutions

• Single-Image Super-Resolution: A Benchmark

Intrinsic Images / Image Super-resolutions

• Ground-truth dataset and baseline evaluations for intrinsic image algorithms

• Intrinsic Images in the Wild

Material Recognition / Image Super-resolutions

• OpenSurface

• Flickr Material Database

Multi-view Reconsturction / Image Super-resolutions

• Multi-View Stereo Reconstruction

Visual Surveillance / Image Super-resolutions

• VIRAT

• CAM2

Change detection / Image Super-resolutions

• ChangeDetection.net

Visual Recognition / Object Detection

• The PASCAL Visual Object Classes

• ImageNet Object Detection Challenge

Visual Recognition / Image Classification

• ImageNet Large Scale Visual Recognition Challenge

Visual Recognition / Scene Recognition

• SUN Database

• Place Dataset

Image Captioning / Image Deblurring

• Microsoft COCO

• Flickr 8K

• Flickr 30K

Visual Recognition / Semantic labeling

• Stanford background dataset

• CamVid

• Barcelona Dataset

• SIFT Flow Dataset

Visual Recognition / Multi-view Object Detection

• 3D Object Dataset

• EPFL Car Dataset

• KTTI Dection Dataset

• SUN 3D Dataset

• PASCAL 3D+

• NYU Car Dataset

Visual Recognition / Fine-grained Visual Recognition

• Fine-grained Classification Challenge

• Caltech-UCSD Birds 200

Visual Recognition / Pedestrian Detection

• Caltech Pedestrian Detection Benchmark

Action Recognition / Video-based

• HOLLYWOOD2 Dataset

Action Recognition / Image Deblurring

• Sun dataset

Resource link collection / Image Deblurring

• Resources for students - Frédo Durand (MIT)

• Advice for Graduate Students - Aaron Hertzmann (Adobe Research)

• Graduate Skills Seminars - Yashar Ganjali, Aaron Hertzmann (University of Toronto)

• Research Skills - Simon Peyton Jones (Microsoft Research)

Writing / Image Deblurring

• Write Good Papers - Frédo Durand (MIT)

• Notes on writing - Frédo Durand (MIT)

• How to Write a Bad Article - Frédo Durand (MIT)

• How to write a good CVPR submission - William T. Freeman (MIT)

• How to write a great research paper - Simon Peyton Jones (Microsoft Research)

• How to write a SIGGRAPH paper - SIGGRAPH ASIA 2011 Course

• Writing Research Papers - Aaron Hertzmann (Adobe Research)

• How to Write a Paper for SIGGRAPH - Jim Blinn

• How to Get Your SIGGRAPH Paper Rejected - Jim Kajiya (Microsoft Research)

• How to write a SIGGRAPH paper - Li-Yi Wei (The University of Hong Kong)

• How to Write a Great Paper - Martin Martin Hering Hering--Bertram (Hochschule Bremen University of Applied Sciences)

• How to have a paper get into SIGGRAPH? - Takeo Igarashi (The University of Tokyo)

• Good Writing - Marc H. Raibert (Boston Dynamics, Inc.)

• How to Write a Computer Vision Paper - Derek Hoiem (UIUC)

Presentation / Image Deblurring

• Giving a Research Talk - Frédo Durand (MIT)

• How to give a good talk - David Fleet (University of Toronto) and Aaron Hertzmann (Adobe Research)

• Designing conference posters - Colin Purrington

Research / Image Deblurring

• How to do research - William T. Freeman (MIT)

• You and Your Research - Richard Hamming

• Warning Signs of Bogus Progress in Research in an Age of Rich Computation and Information - Yi Ma (UIUC)

• Seven Warning Signs of Bogus Science - Robert L. Park

• Five Principles for Choosing Research Problems in Computer Graphics - Thomas Funkhouser (Cornell University)

• How To Do Research In the MIT AI Lab - David Chapman (MIT)

• Recent Advances in Computer Vision - Ming-Hsuan Yang (UC Merced)

• How to Come Up with Research Ideas in Computer Vision? - Jia-Bin Huang (UIUC)

• How to Read Academic Papers - Jia-Bin Huang (UIUC)

Time Management / Image Deblurring

• Time Management - Randy Pausch (CMU)

Links / Image Deblurring

• The Computer Vision Industry - David Lowe

• Cat Paper Collection

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