Fall 2018

Location: Hutchinson Hall 115
Time: MWF 2:10-3:00pm
Units: 4

Instructor: Yong Jae Lee
Email: yongjaelee@ucdavis  (email subject should begin with 
"[ECS 269]")
Office: Academic Surge 2075
Office hours: By appointment

TA: Chongruo Wu
Email: crwu@ucdavis  (email subject should begin with 
"[ECS 269]")
Office hours: By appointment

  • (9/26) Please read this website and the detailed course requirements and grading criteria very carefully.
  • (11/26) The schedule for 12/3-12/7 has been modified due to campus closure on 11/13-11/23.

Course Overview

This graduate seminar course will survey papers in a broad range of topics in computer vision, including object recognition, activity recognition, and scene understanding.  The course goals will be to understand and analyze state-of-the-art techniques, and to identify interesting open questions and future directions.  It should be of relevance to students interested in computer vision and machine learning.


A course in computer vision and a course in machine learning.  Programming will be required for the final project.  Please talk to me if you are unsure if the course is a good match for your background.


The bulk of the course will consist of student paper presentations.  Students will be responsible for writing paper reviews each week, participating in discussions, presenting once in class, and completing a final project.


We will use Canvas for paper review and project proposal/report submissions and grading.  Our class page: https://canvas.ucdavis.edu/courses/289071 


The final grade will be determined by:
  • Paper reviews (25%)
  • Class participation (15%)
  • Paper presentation (30%)
  • Final project (30%)
Important Dates
  • 10/26: Final project proposal due
  • 12/3, 12/5, 12/7: Final project presentations
  • 12/10: Final project report due

Detailed course requirements and grading are here.

 Date  Papers  Presenters
 9/26  Introduction   Yong Jae Lee [pdf]

 9/28  CNN basics I  Yong Jae Lee [pdf]

 10/1  CNN basics II 

 Yong Jae Lee [pdf]

 CNN basics III 
 Yong Jae Lee [pdf]

 10/5  Image Classification

 Deep Residual Learning for Image Recognition. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. CVPR 2016.

 Iman Chatterjee
 Kevin Jesse [pdf]

 Google Cloud Tutorial
 Chongruo Wu [pdf]

 10/10  Object Detection
 Feature Pyramid Networks for Object Detection. Tsung-Yi Lin, Piotr Dollar, Ross Girshick, Kaiming He, Bharath Hariharan, Serge Belongie. CVPR 2017.

 Paulina Lei
 John Nguyen [pdf]

 10/12  Object Detection

 Finding Tiny Faces. Peiyun Hu, Deva Ramanan. CVPR 2017.
 Molly Smith
 Sarahi Arriaga
 Marjan Fariborz [pdf]

 10/15  Segmentation
 Mask R-CNN. Kaiming He, Georgia Gkioxari, Piotr Dollar, Ross Girshick. ICCV 2017.
 Tianchen Sun
 Keshav Dasu [pdf]

 10/17  Pytorch Tutorial

 Chongruo Wu [pdf]

 10/19  People
 Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields. Zhe Cao, Tomas Simon, Shih-En Wei and Yaser Sheikh. CVPR 2017. 

 Yu Su
 Fatemeh Radaei [pdf]

 10/22  People
 Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies, Hanbyul Joo, Tomas Simon, and Yaser Sheikh, CVPR 2018.
 Shraddha Agrawal
 Ashwin Bhandare
 Yicheng Lin [pdf]

 10/24  Visualizing CNNs

 Network Dissection: Quantifying Interpretability of Deep Visual Representations. David Bau*, Bolei Zhou*, Aditya Khosla, Aude Oliva, Antonio Torralba. CVPR 2017.

 Xiaoyu Zhang
 Jing Li
 Qingxiaoyang Zhu 

 10/26  Final project proposal due


Efficient Optimization for Rank-Based Loss Functions. Pritish Mohapatra, Michal Rolínek, C.V. Jawahar, Vladimir Kolmogorov, M. Pawan Kumar, CVPR 2018.

 Muting Wu
 Jiyu Chen [pdf]

 10/29  Optimization

Group Normalization. Yuxin Wu, Kaiming He, ECCV 2018.

 Tianran Wang
 Xueyan Zou
 Zhiyang Lin [pdf]

 10/31  Neural Network Art

 Image Style Transfer Using Convolutional Neural NetworksL. Gatys, A. Ecker, M. Bethge. CVPR 2016.

 Antara Bhowmick
 Prerit Auti
 Anshi Agarwal [pdf]

 11/2  Generative Adversarial Networks

Image-to-Image Translation with Conditional Adversarial Networks. Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros. CVPR 2017.

 Lahiru Chamain   Hewa Gamage
 + Alex Shakouri
 + Chi Po Choi [pdf]

 11/5  Generative Adversarial Networks

 GANimation: Anatomically-aware Facial Animation from a Single Image.  Albert Pumarola, Antonio Agudo, Aleix M. Martinez, Alberto Sanfeliu, Francesco Moreno-Noguer, ECCV 2018.

 Yu Li
 Yuchu Lei
 Ming Wang [pdf]

 11/7  Transfer Learning

 Taskonomy: Disentangling Task Transfer Learning.  Amir R. Zamir, Alexander Sax, William Shen, Leonidas J. Guibas, Jitendra Malik, and Silvio Savarese. CVPR 2018. 
 Yifei Teng
 Chuan He
 Weiyan Shi [pdf]

 11/9  3D
SPLATNet: Sparse Lattice Networks for Point Cloud Processing. Hang Su, Varun Jampani, Deqing Sun, Subhransu Maji, Evangelos Kalogerakis, Ming-Hsuan Yang, Jan Kautz, CVPR 2018.
 Vivian Vuong
 Yalin Zhang
 Kun Qian [pdf]

 11/12  No class - Veteran's Day  

 11/14  No class - campus closure due to poor air quality  

 11/16  No class - campus closure due to poor air quality   

 11/19  No class - campus closure due to poor air quality  

 11/21  No class - campus closure due to poor air quality  

 11/23  No class - Thanksgiving  

 11/26  Self supervision

 Self-supervised Tracking by Colorization (Tracking Emerges by Colorizing Videos). Carl Vondrick*, Abhinav Shrivastava, Alireza Fathi, Sergio Guadarrama, Kevin Murphy, ECCV 2018.
 Yangming Wen
 Kurt Schneider
 Jiarui Wang [pdf]

 11/28  Graph Matching

Deep Learning of Graph Matching, Andrei Zanfir, Cristian Sminchisescu, CVPR 2018.
 Bokun Wang
 Yue Wu
 Xincheng Lei [pdf]

 11/30  Curiosity 

Large-Scale Study of Curiosity-Driven Learning. Yuri Burda, Harri Edwards, Deepak Pathak, Amos Storkey, Trevor Darrell and Alexei A. Efros. arXiv 2018. 
 + Matthew Lyons
 + Navinkumar Nitin
     Adhe [pdf]

 12/3  Final Project Presentations


 Implicit 3D Orientation Learning for 6D Object Detection from RGB Images. Martin Sundermeyer, Zoltan Marton, Maximilian Durner, Manuel Brucker ,Rudolph Triebel, ECCV 2018.

 Alireza Mounesisohi
 Heqiao Ruan [pdf]

 12/5  Final Project Presentations

 Domain Adaptation

 Open Set Domain Adaptation.  Pau Panareda Busto, Juergen Gall, ICCV 2017.

 Yue Zhang
 Yinhao Jiang
 Chong Zhou [pdf]

 12/7  Final Project Presentations


 Annotating Object Instances with a Polygon-RNN. Lluís Castrejón, Kaustav Kundu, Raquel Urtasun, Sanja Fidler, CVPR 2017.

 Qingyang Wu
 Jing Gu
 Yuheng Li [pdf]


This course has been inspired by the following courses:

Subpages (1): Requirements