Seokyun Ha

Kubernetes Lover
CS && MATH


[목차]

Preliminary

  • Linear Algebra
  • Bayes’ Theorem


Image Classification

Image Processing Introduction

  • Convolution
    • smoothing
      • Bilinear
      • Average
      • Gaussian
  • Edge
    • Gradient Image
  • Corners: Harris Corner Detection
    • Eigen Decomposition
  • Blob
    • Laplace of Gaussian; LoG


Image Classification + CV

  • SIFT (2004)
  1. Finding Scale-Space Extrema
  2. Keypoint Filtering
  3. Orientation Assignment
  4. Calculating Descriptor
  • Spatial Pytramid Matching (2006)
  • Discrimative vs. Geneartive Model


Image Classification + DL

  • MLP
  • Loss Functions
  • Gradient Descent
    • SGD
    • Momentum
  • CNN
  • Overfitting Issue
    • Drop out
    • Weight decay
    • Early Stopping
    • Network Initialization
      • Learning from scratch
      • Xavier Initialization (2010)
      • He Initialization (2015)


CNN Architectures

  • LeNet (1998)
  • AlexNet
    • LRN; Local response Normalizatioin
  • VGGNet (2014)
  • ResNet (2016)
    • Degrading Problem
    • Skip Connection
    • Batch Normalization (2015)
  • Beyond ResNet
    • DenseNet (2017)
      • Channel-wise concatenation
    • SENet (2017)
      • Squeeze & Excitation


Object Detection

  • Support Vector Machine
    • Linear SVM + Separable Case
    • Linear SVM + Non-Separable Case
      • Soft margin
    • Non-Linear SVM
      • Kernel Method
    • Multi-Class SVM
  • Pedestrian Detection + SVM (2005)
    • HOG Histogram of Orientated Gradient+ SVM


  • R-CNN Region-base CNN (2014)
    • Object proposal
      • Selective Search
  • Fast R-CNN (2015)
    • ROI pooling
  • Faster R-CNN (2015)
    • Fast R-CNN + RPN Region Proposal Network


Semantic Segmentation

  • Fully Convolutional Network (FCN Family)
    • FCN (2015)
    • DeepLab
  • Convolutional Encoder-Decoders
    • U-Net
    • DeConvNet (2015)
  • FCN (2015)
    • 1x1 conv
    • adding skip connection
  • DeepLab (2017)
    • Atrous Convolution
    • CRF; Fully-Connected Conditional Random Field
  • Pyramid Scene Parsing Network (2017)
    • Pyramid pooling module
  • Context Encoding Network (2018)
    • Attention module


  • DeConvNet (2015)
    • conv - deconv
    • pooling - unpooling

Instance-aware Semantic Segmentation

  • Multi-task Network Cascades (2016)
  • Multi-scale Patch Aggregation (2016)
  • Mask R-CNN (2017)
    • ROI Align


Metric Learning


Video Vision

Video Classification + CV

  • Optical Flow
    • (가정) Color constancy
    • (가정) Small motion
    • Lukas-Kanade Flow
  • STIP; Space-Time Interest Point (2005)
  • Dense Trajectory

Video Classification + DL

  • 3D CNN (2010)
  • C3D (2015)
  • Time Information Fusion (2014)
    • Sing Frame
    • Late Fusion
    • Early Fusion
    • Slow Fusion
  • Two-Stream Cconvolutional Network (2014)


Visual Tracking


Model Fitting

  • Least Square
    • Ordinary Linear Least Square
    • Total Linear Least Square
  • RANSAC RANdom SAmple Consensus
  • Hough Transform


Camera Models

  • 2D Objects
  • 2D Transformations
    • Translation
    • Euclidean transform
    • Similarity transform
    • Affine transform
    • Projective transform
  • 3D Objects
    • homogeneous coordinates; $\overline{x} = [x, y, z, 1]$
  • Pinhole Model
    • Intrinsic Parameters
    • Extrinsic Parameters
  • Camera Clibration
    • Estimate camera parameters matrix