Instructor: Prof. Yen-Yu Lin
Visual recognition aims to enable computers to see, understand, and interpret the world like human visual systems. Deep learning technologies are at the core of the current machine vision revolution. Large-scale annotated data and affordable GPU hardware jointly allow the training of deep learning models with hundreds of layers and millions of parameters, which greatly improve the performance of various machine vision applications and even initiate new vision applications.
Thursday 3:00 pm ~ 4:00 pm at EC118
Please contact instructor Yen-Yu Lin at lin@cs.nctu.edu.tw or TA Jimmy Yang at d08922002@ntu.edu.tw
- 4 homework assignments: 72%, see HW READEME
- Final project: 28%
| Week | Date | Topic | Remarks |
|---|---|---|---|
| 1 | 09/12 | Introduction to Visual Recognition | |
| 2 | 09/19 | Conventional Machine Learning vs. Deep Learning | |
| 3 | 09/26 | Convolutional Neural Networks (CNN) | HW1 anoounce |
| 4 | 10/03 | Representative CNN Architectures | |
| 5 | 10/10 | National Holiday (Double tenth) | |
| 6 | 10/17 | Generative Adversarial Learning and Recurrent Neural Networks | HW1 due, HW2 announce |
| 7 | 10/24 | Object Detection / Semantic Segmentation | |
| 8 | 10/31 | Guest Lectures | |
| 9 | 11/07 | Semantic Segmentation | HW2 due, HW3 announce |
| 10 | 11/14 | Image Super-resolution | |
| 11 | 11/21 | Image Matching and Alignment | |
| 12 | 11/28 | Action and Gesture Recognition | HW3 due, Final project announce, HW4 announce |
| 13 | 12/05 | 3D Point Classification and Segmentation | |
| 14 | 12/12 | Guest Lectures II | |
| 15 | 12/19 | Image Style Transfer, Video Frame Interpolation and Video Synthesis | HW4 due |
| 16 | 12/26 | Final project presentation I | |
| 17 | 01/02 | Final project presentation II |