ECE59500CV
Deep Learning for Computer Vision
Fall 2021
General Information
Lectures: M,W,F 3:30pm - 4:20pm, WALC 3154
Instructor:
Jeffrey Mark Siskind,
EE313e, 765/496-3197,
qobi@purdue.edu
Office Hours: T 5:00pm - 6:00pm, EE313e
ece59500cv-students-list@ecn.purdue.edu
ece59500cv-staff-list@ecn.purdue.edu
Syllabus
Brightspace
BibTeX file for papers we will cover in this course
github repository
Web site for Fall 2020 offering
deep learning
segmentation
object classification and localization
activity classification and localization
semantic segmentation
depth reconstruction
3D reconstruction
generative adversarial networks
image and video captioning
image and video retrieval
- Lecture 1: Course Overview
Monday 23 August 2021
Whiteboard
- Lecture 2: Automatic Differentiation---I
A.G. Baydin,
B.A. Pearlmutter,
A.A. Radul, and
J.M. Siskind,
`Automatic differentiation in machine learning: a survey,'
Journal of Machine Learning Research (JMLR),
18(153):1-43,
2018.
Wednesday 25 August 2021
Whiteboard
- Lecture 3: Automatic Differentiation---II
Friday 27 August 2021
Whiteboard
forward_mode.py
newton_raphson.py
- Lecture 4: Automatic Differentiation---III
Monday 30 August 2021
Whiteboard
- Lecture 5: Automatic Differentiation---IV
Wednesday 1 September 2021
Whiteboard
- Lecture 6: Automatic Differentiation---V
Friday 3 September 2021
Whiteboard
- Lecture 7: Automatic Differentiation---VI
B.A. Pearlmutter and
J.M. Siskind,
`Reverse-Mode AD in a functional framework:
Lambda the Ultimate Backpropagator,'
ACM Transactions on Programming Languages and Systems (TOPLAS),
30(2):1-36,
2008.
Wednesday 8 September 2021
Whiteboard
- Lecture 8: Automatic Differentiation---VII
J.M. Siskind and
B.A. Pearlmutter,
`Nesting forward-mode AD in a functional framework,'
Higher-Order and Symbolic Computation (HOSC),
21(4):361-376,
2008.
Friday 10 September 2021
Whiteboard
- Lecture 9: Automatic Differentiation---VIII
Monday 13 September 2021
Whiteboard
- Lecture 10: Automatic Differentiation---IX
Wednesday 15 September 2021
Whiteboard
- Lecture 11: Automatic Differentiation---X
Friday 17 September 2021
Whiteboard
tracing.py
reverse_mode.py
- Lecture 12: Automatic Differentiation---XI
Monday 20 September 2021
Whiteboard
gui.py
linear_classifier.py
linear_classifier_gui.py
linear_classifier_pytorch_gui.py
two_layer_perceptron.py
two_layer_perceptron_gui.py
two_layer_perceptron_pytorch_gui.py
- Lecture 13: Model-Based Vision
D.G. Lowe,
`Three-dimensional object recognition from single two-dimensional images,'
Artificial Intelligence (AIJ),
31(3):355-395,
1987.
Wednesday 22 September 2021
Whiteboard
- Lecture 14: Histograms of Oriented Gradients
N. Dalal and
B. Triggs,
`Histograms of oriented gradients for human detection,'
Computer Vision and Pattern Recognition (CVPR),
pp. 886-893,
2005.
Friday 24 September 2021
Whiteboard
- Lecture 15: Deformable Part Models
P.F. Felzenszwalb,
R.B. Girshick,
D. McAllester, and
D Ramanan,
`Object detection with discriminatively trained part-based models,'
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI),
32(9):1627-1645,
2010.
Monday 27 September 2021
Whiteboard
- Lecture 16: AlexNet
A. Krizhevsky,
I. Sutskever, and
G.E. Hinton,
`ImageNet classification with deep convolutional neural networks,'
Advances in Neural Information Processing Systems (NeurIPS),
pages 1097-1105,
2012.
Wednesday 29 September 2021
Whiteboard
- Lecture 17: VGG-16
K. Simonyan and
A. Zisserman,
`Very deep convolutional networks for large-scale image recognition,'
International Conference on Learning Representations (ICLR),
2015.
Friday 1 October 2021
Whiteboard
- Lecture 18: Inception v1
C. Szegedy,
W. Liu,
Y. Jia,
P. Sermanet,
S. Reed,
D. Anguelov,
D. Erhan,
V. Vanhoucke, and
A. Rabinovich,
`Going deeper with convolutions,'
Computer Vision and Pattern Recognition (CVPR),
2015.
Monday 4 October 2021
Whiteboard
- Lecture 19: Batch Normalization
S. Ioffe and
C. Szegedy,
`Batch normalization: accelerating deep network training by reducing internal
covariate shift,'
International Conference on Machine Learning (ICML),
pp. 448-456,
2015.
Wednesday 6 October 2021
Whiteboard
- Lecture 20: ResNet
K. He,
X. Zhang,
S. Ren, and
J. Sun,
`Deep residual learning for image recognition,'
Computer Vision and Pattern Recognition (CVPR),
pp. 770-778,
2016.
Friday 8 October 2021
Whiteboard
- Lecture 21: Inception v3
C. Szegedy,
V. Vanhoucke,
S. Ioffe,
J. Shlens, and
Z. Wojna,
`Rethinking the Inception architecture for computer vision,'
Computer Vision and Pattern Recognition (CVPR),
pp. 2818-2826,
2016.
Wednesday 13 October 2021
Whiteboard
- Lecture 22: No class
Friday 15 October 2021
- Lecture 23: DenseNet
G. Huang,
Z. Liu,
L. Van Der Maaten, and
K.Q. Weinberger,
`Densely connected convolutional networks,'
Computer Vision and Pattern Recognition (CVPR),
pp. 4700-4708,
2017.
Monday 18 October 2021
Whiteboard
- Lecture 24: R-CNN
R. Girshick,
J. Donahue,
T. Darrell, and
J. Malik,
`Rich feature hierarchies for accurate object detection and semantic
segmentation,'
Computer Vision and Pattern Recognition (CVPR),
pp. 580-587,
2014.
Wednesday 20 October 2021
Whiteboard
- Lecture 25: Fast R-CNN
R. Girshick,
`Fast R-CNN,'
Computer Vision and Pattern Recognition (CVPR),
pp. 1440-1448,
2015.
Friday 22 October 2021
Whiteboard
- Lecture 26: Faster R-CNN
S. Ren,
K. He,
R. Girshick, and
J. Sun,
`Faster R-CNN: Towards real-time object detection with region proposal
networks,'
Advances in Neural Information Processing Systems (NeurIPS),
pp. 91-99,
2015.
Monday 25 October 2021
Whiteboard
- Lecture 27: YOLO
J. Redmon,
S. Divvala,
R. Girshick, and
A. Farhadi,
`You only look once: Unified, real-time object detection,'
Computer Vision and Pattern Recognition (CVPR),
pp. 779-788,
2016.
Wednesday 27 October 2021
Whiteboard
- Lecture 28: No class
Friday 29 October 2021
- Lecture 29: SSD
W. Liu,
D. Anguelov,
D. Erhan,
C. Szegedy,
S. Reed,
C.-Y. Fu, and
A.C. Berg,
`SSD: Single shot multibox detector,'
European Conference on Computer Vision (ECCV),
pp. 21-37,
2016.
Monday 1 November 2021
Whiteboard
- Lecture 30: Mask R-CNN
K. He,
G. Gkioxari,
P. Dollar, and
R. Girshick,
`Mask R-CNN,'
International Conference on Computer Vision (ICCV),
pp. 2961-2969,
2017.
Wednesday 3 November 2021
Whiteboard
- Lecture 31: FPN
T.-Y. Lin,
P. Dollar,
R. Girshick,
K. He,
B. Hariharan, and
S. Belongie,
`Feature pyramid networks for object detection,'
Computer Vision and Pattern Recognition (CVPR),
pp. 2117-2125,
2017.
Friday 5 November 2021
Whiteboard
- Lecture 32: YOLO v2
J. Redmon and
A. Farhadi,
`YOLO9000: better, faster, stronger,'
Computer Vision and Pattern Recognition (CVPR),
pp. 7263-7271,
2017.
Monday 8 November 2021
Whiteboard
- Lecture 33: DeepVideo
A. Karpathy,
G. Toderici,
S. Shetty,
T. Leung,
R. Sukthankar, and
L. Fei-Fei,
`Large-scale video classification with convolutional neural networks,'
Computer Vision and Pattern Recognition (CVPR),
pp. 1725-1732,
2014.
Wednesday 10 November 2021
Whiteboard
- Lecture 34: Student Presentations
Friday 12 November 2021
Whiteboard
- Lecture 35: No class
Monday 15 November 2021
- Lecture 36: Student Presentations
Wednesday 17 November 2021
Whiteboard
- Lecture 37: Student Presentations
Friday 19 November 2021
Whiteboard
- Lecture 38: Student Presentations
Monday 22 November 2021
Whiteboard
- Lecture 39: Student Presentations
Monday 29 November 2021
Whiteboard
- Lecture 40: Student Presentations
Wednesday 1 December 2021
Whiteboard
- Lecture 41: Student Presentations
Friday 3 December 2021
Whiteboard
- Lecture 42: Student Presentations
Monday 6 December 2021
Whiteboard
- Lecture 43: Student Presentations
Wednesday 8 December 2021
Whiteboard
- Lecture 44: Student Presentations
Friday 10 December 2021
Whiteboard
ECE59500CV | Elmore Family ECE | Purdue College of Engineering | Purdue University