Object Classification Seminar

NOTE: Please send requests for lectures between the end of the first meeting until the end of the second meeting. List at least 3 options in decreasing order.

Lecture 1 – Introduction

Presenter: Rita Osadchy

• Introduction
• Structure of the Seminar

Slides: pdf

Lecture 2 (no meeting)

Presenter: Rita Osadchy

• Lecture assignment

Lecture 3 – Pre-Deep Learning Object Recognition

Date : 17/03

Presenter: פידאא שקיר, לידיא אבו סאלח

Reading List:

· Object Recognition from Local Scale-Invariant Features, Lowe, ICCV 1999.  [pdf] 

· Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, Lazebnik, Schmid, and Ponce, CVPR [pdf].

Lecture 4 – Object Classification with CNNs

Date: 7/04

Presenter: אור אשכנזי, שגיא גוילי

Reading List:

Give some intro on CNN first then present:

• K. Simonyan and A. Zisserman Very Deep Convolutional Networks for Large-Scale Image Recognition ICLR 2015 [pdf]
• K. He, X. Zhang, S. Ren, and J. Sun: Deep Residual Learning for Image Recognition [pdf]

Lecture 5 – Object Detection

Date: 21/04

Presenter: יוני מרקו, ליאת דוד

Reading Material:

· Rich feature hierarchies for accurate object detection and semantic segmentation.  R. Girshick et al.  CVPR 2013 [pdf] -- the detection part

· Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun [pdf]

An overview of these methods [here]

Lecture 6–Transfer Learning and One/Few shot learning

Date: 28/04

Presenter: Dima Nakhleh, Mikhael Bikman

Reading Material:

· http://cs231n.github.io/transfer-learning/

· G. Koch, R. Zemel, and R. Salakhutdinov Siamese Neural Networks for One-shot Image Recognition [pdf]

· Prototypical Networks for Few-shot Learning, Jake Snell, Kevin Swersky, Richard S. Zemel [pdf]

Lecture 7 – Attributes and Parts and Zero-Shot Learning

Date: 5/05

Presenter: שאדי הלון, פארוק כריים

Reading Material:

· Describing Objects by Their Attributes, A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth, CVPR 2009. [pdf]

• Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer, C. Lampert, H. Nickisch, and S. Harmeling, CVPR 2009  [pdf]

Lecture – Faces

Date:

Presenter:

Reading Material:

· Mei Wang, Weihong Deng: Deep Face Recognition: A Survey [pdf]

Lecture 8 – Language and Vision   

Date: 12/05

Presenter: Basil Sgier, עלי עבד אלחלים

Reading Material

· Andrej Karpathy Li Fei-Fei. Deep Visual-Semantic Alignments for Generating Image Descriptions CVPR 2015 [pdf] [project]

· Jiasen Lu et al., “Hierarchical Question-Image Co-Attention for Visual Question Answering” [pdf]

Lecture 9 – Video Classification

Date: 19/05

Presenter: ענבר כהן, שגיא פנצל

Reading Material:

· Kapathy et al.: Large‐scale Video Classification with Convolutional Neural Networks. CVPR 2014 [pdf]

· K. Simonyan, A. Zissermann: Two‐Stream Convolutional Networks for Action Recognition in Videos. NIPS 2014 [pdf]

Lecture 10 – Continual Learning, Augmentation

Date: 26/05

Presenter: Deborah Levy

Reading Material:

· James Kirkpatrick et al., “Overcoming catastrophic forgetting in neural networks” [pdf]

Presenter: Dvir Kovas

Reading Material:

· Introduction to GAN https://pathmind.com/wiki/generative-adversarial-network-gan (only part about GAN)

· Antreas Antoniou, Amos Storkey, Harrison Edwards, “Data augmentation generative adversarial networks” [pdf]

· Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros, “Unpaired image-to-image translation using cycle-consistent adversarial networks” [pdf]