机器视觉

Awesome Computer Vision: Awesome

受启发的精选计算机视觉资源精选清单 awesome-php.

有关列出其学术谱系的计算机视觉人士的列表,请访问 here

Contributing

请随时发给我 pull requests 或通过电子邮件(jbhuang@vt.edu)添加链接.

Awesome Lists

Books

Computer Vision

OpenCV Programming

  • Learning OpenCV: Computer Vision with the OpenCV Library -加里·布拉德斯基(Gary Bradski)和阿德里安·凯勒(Adrian Kaehler)
  • Practical Python and OpenCV -阿德里安·罗斯布鲁克(Adrian Rosebrock)
  • OpenCV Essentials -奥斯卡·丹尼兹·苏亚雷斯(Oscar Deniz Suarez),米德尔·米拉格罗·费尔南德斯·卡洛布莱斯(Mel del Milagro Fernandez Carrobles),诺伊莉亚·瓦莱兹·诺埃纳(Noelia Vallez Enano),格洛里亚·布埃诺·加西亚(Illael Serrano Gracia)

Machine Learning

Fundamentals

Courses

Computer Vision

Computational Photography

Machine Learning and Statistical Learning

Optimization

Papers

Conference papers on the web

Survey Papers

## 预训练的计算机视觉模型 * List of Computer Vision models 这些模型在自定义对象上训练

Tutorials and talks

Computer Vision

Recent Conference Talks

3D Computer Vision

Internet Vision

Computational Photography

Learning and Vision

Object Recognition

Graphical Models

Machine Learning

Optimization

Deep Learning

Software

Annotation tools

General Purpose Computer Vision Library

Multiple-view Computer Vision

Feature Detection and Extraction

  • VLFeat
  • SIFT
  • David G. Lowe,“尺度不变关键点的独特图像特征”,《国际计算机视觉杂志》,第60卷,第2期(2004年),第91-110页.
  • SIFT++
  • BRISK
  • Stefan Leutenegger,Margarita Chli和Roland Siegwart,“ BRISK:二进制鲁棒不变可扩展关键点”,ICCV 2011
  • SURF
  • Herbert Bay,Andreas Ess,Tinne Tuytelaars,Luc Van Gool,“ SURF:加快了鲁棒的功能”,《计算机视觉与图像理解(CVIU)》,第1卷. 110,No.3,pp.346--359,2008年
  • FREAK
  • A. Alahi,R.Ortiz和P. Vandergheynst,“怪胎:快速视网膜关键点”,CVPR 2012
  • AKAZE
  • Pablo F. Alcantarilla,Adrien Bartoli和Andrew J. Davison,“ KAZE功能”,ECCV 2012
  • Local Binary Patterns

High Dynamic Range Imaging

Semantic Segmentation

Low-level Vision

Stereo Vision
Optical Flow
Image Denoising

BM3D,KSVD,

Super-resolution
  • Multi-frame image super-resolution *皮卡,多帧图像超分辨率的LC机器学习,博士学位论文2008
  • Markov Random Fields for Super-Resolution
    • W. T. Freeman和C. Liu. 用于超分辨率和纹理合成的马尔可夫随机场. 摘自A. Blake,P.Kohli和C. Rother编,《视觉和图像处理的马尔可夫随机场的进展》,第10章,麻省理工学院出版社,2011年
  • Sparse regression and natural image prior
    • KI Kim和Y. Kwon,“使用稀疏回归和自然图像先验的单图像超分辨率”,IEEE Trans. 模式分析和机器智能,第一卷. 32号 6,第1127-1133页,2010年.
  • Single-Image Super Resolution via a Statistical Model
    • T. Peleg和M. Elad,基于稀疏表示的单图像超分辨率统计预测模型,《 IEEE Transactions on Image Processing》,第1卷. 23,No.6,Pages 2569-2582,2014年6月
  • Sparse Coding for Super-Resolution
    • R.Zeyde,M.Elad和M.Protter,使用稀疏表示法,曲线和曲面进行单幅图像放大,法国阿维尼翁,2010年6月24日至30日(也出现在计算机上的讲义中,科学-LNCS).
  • Patch-wise Sparse Recovery *杨建超,约翰·赖特,托马斯·黄和马一. 通过稀疏表示实现图像超分辨率. IEEE Transactions on Image Processing(TIP),第一卷 19,第11期,2010年.
  • Neighbor embedding
    • H. Chang,DY DY Yeung,Y.Xiong. 通过邻居嵌入实现超分辨率. IEEE计算机协会计算机视觉和模式识别(CVPR)会议论文集,第1卷,第275-282页,美国华盛顿特区,2004年6月27日至7月2日.
  • Deformable Patches
    • Yu Zhu, Yanning Zhang and Alan Yuille, Single Image Super-resolution using Deformable Patches, CVPR 2014
  • SRCNN *董冬,Chen Change Loy,何凯明,唐小鸥,学习深度卷积网络以实现图像超分辨率,在ECCV 2014中
  • A+: Adjusted Anchored Neighborhood Regression
    • R. Timofte,V.De Smet和L. Van Gool. A +:经过调整的锚定邻域回归以实现快速超分辨率,ACCV 2014
  • Transformed Self-Exemplars *黄佳斌,Abhishek Singh和Narendra Ahuja,使用变换后的自样本的单图像超分辨率,IEEE计算机视觉和模式识别会议,2015年
Image Deblurring

非盲反卷积 * 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

盲反卷积 * 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

非均匀去模糊 * 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

Image Completion
Image Retargeting
Alpha Matting
Image Pyramid
Edge-preserving image processing

Intrinsic Images

Contour Detection and Image Segmentation

Interactive Image Segmentation

Video Segmentation

Camera calibration

Simultaneous localization and mapping

SLAM community:
Tracking/Odometry:
Graph Optimization:
Loop Closure:
Localization & Mapping:

Single-view Spatial Understanding

Object Detection

Nearest Neighbor Field Estimation

Visual Tracking

Saliency Detection

Attributes

Action Reconition

Egocentric cameras

Human-in-the-loop systems

Image Captioning

Optimization

  • Ceres Solver -非线性最小二乘问题和无约束优化求解器
  • NLopt-非线性最小二乘问题和无约束优化求解器
  • OpenGM -基于因子图的离散优化和推理求解器
  • GTSAM -基于因子图的租约平方优化求解器

Deep Learning

Machine Learning

Datasets

Low-level Vision

Stereo Vision
Optical Flow
Video Object Segmentation
Change Detection
Image Super-resolutions

Intrinsic Images

Material Recognition

Multi-view Reconsturction

Saliency Detection

Visual Tracking

Visual Surveillance

Saliency Detection

Change detection

Visual Recognition

Image Classification
Scene Recognition
Object Detection
Semantic labeling
Multi-view Object Detection
Fine-grained Visual Recognition
Pedestrian Detection

Action Recognition

Image-based
Video-based
Image Deblurring

Image Captioning

Scene Understanding

# SUN RGB-D -RGB-D场景理解基准套件 # NYU depth v2 -从RGBD图像进行室内分割和支持推断

Aerial images

# Aerial Image Segmentation -从在线地图上学习航空图像分割

Resources for students

Writing

Presentation

Research

Time Management

Blogs

Songs

Licenses

License

CC0

在法律允许的范围内, Jia-Bin Huang 放弃了此作品的所有版权以及相关或邻近的权利.