Learn · Modern Computer Vision
Lecture 86 of 90week-12
Deepnets for Segmentation and OF -2
Prof. A. N. Rajagopalan · IIT Madras
Credits and licence
- From
- Modern Computer Vision, IIT Madras (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- Tweens profiles and older. How courses are placed
All the lectures
- Course introduction - 1
- Course introduction - 2
- Introduction to Deep Learning - 1
- Introduction to Deep Learning - 2
- Introduction to Deep Learning - 3
- Introduction to Neuron - 1
- Introduction to Neuron - 2
- Introduction to Neuron - 3
- Multilayer Perceptron
- Regression and classification losses
- Training a neural network
- Gradient descent
- Activation function
- Backpropagation in MLP - 1
- Backpropagation in MLP - 2
- Optimization and Regularization - 1
- Optimization and Regularization - 2
- Regularization
- Dropout
- Pre-processing
- Convolutional Neural Networks - 1
- Convolutional Neural Networks - 2
- Convolutional Neural Networks - 3
- CNN Properties
- Alexnet
- CNN Architectures - 1
- CNN Architectures - 2
- CNN Architectures - 3
- Introduction to RNN - 1
- Introduction to RNN - 2
- Encoder-Decoder models in RNN
- LSTM
- Low-level vision - 1
- Low-level vision - 2
- Low-level vision - 3
- Spatial Domain Filtering
- Frequency Domain Filtering
- Edge Detection - 1
- Edge Detection - 2
- DeepNets for Edge Detection
- Line detection
- Feature detectors
- Harris Corner Detector - 1
- Harris Corner Detector - 2
- Harris Corner Detector - 3
- Blob detection - 1
- Blob detection - 2
- Blob detection - 3
- SIFT - 1
- SIFT - 2
- Feature descriptors - 1
- Feature descriptors - 2
- SURF - 1
- SURF - 2
- Single-View Geometry - 1
- Single-View Geometry - 2
- 2D Geometric transformations - 1
- 2D Geometric transformations - 2
- Camera intrinsics and extrinsics - 1
- Camera intrinsics and extrinsics - 2
- Two-view stereo - 1
- Two-view stereo - 2
- Two-view stereo - 3
- Algebraic representation of epipolar geometry - 1
- Algebraic representation of epipolar geometry - 2
- Fundamental matrix computation - 1
- Fundamental matrix computation - 2
- Structure from Motion - 1
- Structure from Motion - 2
- Structure from Motion - 3
- Batch processing in SFM
- Multi-view SFM
- Factorization methods in SFM
- Bundle adjustment
- Dense 3D reconstruction
- Some results in Stereo and SFM
- Deepnets for stereo and SFM - 1
- Deepnets for stereo and SFM - 2
- Mid-level vision - 1
- Mid-level vision - 2
- Lucas-Kanade method for OF
- Handling large motion in optical flow
- Image segmentation
- GMM for clustering
- Deepnets for Segmentation and OF -1
- Deepnets for Segmentation and OF -2
- Deepnets for Segmentation and OF -3
- Deepnets for Object Detection - 1
- Deepnets for Object Detection - 2
- Vision and Language