NOC:Modern Computer Vision

Lecture 1 - Course introduction - 1

Lecture 2 - Course introduction - 2

Lecture 3 - Introduction to Deep Learning - 1

Lecture 4 - Introduction to Deep Learning - 2

Lecture 5 - Introduction to Deep Learning - 3

Lecture 6 - Introduction to Neuron - 1

Lecture 7 - Introduction to Neuron - 2

Lecture 8 - Introduction to Neuron - 3

Lecture 9 - Multilayer Perceptron

Lecture 10 - Regression and classification losses

Lecture 11 - Training a neural network

Lecture 12 - Gradient descent

Lecture 13 - Activation function

Lecture 14 - Backpropagation in MLP - 1

Lecture 15 - Backpropagation in MLP - 2

Lecture 16 - Optimization and Regularization - 1

Lecture 17 - Optimization and Regularization - 2

Lecture 18 - Regularization

Lecture 19 - Dropout

Lecture 20 - Pre-processing

Lecture 21 - Convolutional Neural Networks - 1

Lecture 22 - Convolutional Neural Networks - 2

Lecture 23 - Convolutional Neural Networks - 3

Lecture 24 - CNN Properties

Lecture 25 - Alexnet

Lecture 26 - CNN Architectures - 1

Lecture 27 - CNN Architectures - 2

Lecture 28 - CNN Architectures - 3

Lecture 29 - Introduction to RNN - 1

Lecture 30 - Introduction to RNN - 2

Lecture 31 - Encoder-Decoder models in RNN

Lecture 32 - LSTM

Lecture 33 - Low-level vision - 1

Lecture 34 - Low-level vision - 2

Lecture 35 - Low-level vision - 3

Lecture 36 - Spatial Domain Filtering

Lecture 37 - Frequency Domain Filtering

Lecture 38 - Edge Detection - 1

Lecture 39 - Edge Detection - 2

Lecture 40 - DeepNets for Edge Detection

Lecture 41 - Line detection

Lecture 42 - Feature detectors

Lecture 43 - Harris Corner Detector - 1

Lecture 44 - Harris Corner Detector - 2

Lecture 45 - Harris Corner Detector - 3

Lecture 46 - Blob detection - 1

Lecture 47 - Blob detection - 2

Lecture 48 - Blob detection - 3

Lecture 49 - SIFT - 1

Lecture 50 - SIFT - 2

Lecture 51 - Feature descriptors - 1

Lecture 52 - Feature descriptors - 2

Lecture 53 - SURF - 1

Lecture 54 - SURF - 2

Lecture 55 - Single-View Geometry - 1

Lecture 56 - Single-View Geometry - 2

Lecture 57 - 2D Geometric transformations - 1

Lecture 58 - 2D Geometric transformations - 2

Lecture 59 - Camera intrinsics and extrinsics - 1

Lecture 60 - Camera intrinsics and extrinsics - 2

Lecture 61 - Two-view stereo - 1

Lecture 62 - Two-view stereo - 2

Lecture 63 - Two-view stereo - 3

Lecture 64 - Algebraic representation of epipolar geometry - 1

Lecture 65 - Algebraic representation of epipolar geometry - 2

Lecture 66 - Fundamental matrix computation - 1

Lecture 67 - Fundamental matrix computation - 2

Lecture 68 - Structure from Motion - 1

Lecture 69 - Structure from Motion - 2

Lecture 70 - Structure from Motion - 3

Lecture 71 - Batch processing in SFM

Lecture 72 - Multi-view SFM

Lecture 73 - Factorization methods in SFM

Lecture 74 - Bundle adjustment

Lecture 75 - Dense 3D reconstruction

Lecture 76 - Some results in Stereo and SFM

Lecture 77 - Deepnets for stereo and SFM - 1

Lecture 78 - Deepnets for stereo and SFM - 2

Lecture 79 - Mid-level vision - 1

Lecture 80 - Mid-level vision - 2

Lecture 81 - Lucas-Kanade method for OF

Lecture 82 - Handling large motion in optical flow

Lecture 83 - Image segmentation

Lecture 84 - GMM for clustering

Lecture 85 - Deepnets for Segmentation and OF -1

Lecture 86 - Deepnets for Segmentation and OF -2

Lecture 87 - Deepnets for Segmentation and OF -3

Lecture 88 - Deepnets for Object Detection - 1

Lecture 89 - Deepnets for Object Detection - 2

Lecture 90 - Vision and Language