News

Please check the blackboard for up-to-date announcements!

[20/02/19]

• Please check the Lectures below for lecture slides on Optical Flow Estimation.
• You can also find the list of papers and the pdf/code/talk related to them.
• Please read all of the papers and participate in the discussions.
• Please do not forget to submit your project proposal by Friday.

[20/02/12]

• You can find the presentation on Stereo Estimation below in the table.
• Please check the Lectures below for tutorials and lecture slides on Multi-view Reconstruction.
• You can also find the list of papers and the pdf/code/talk related to them.
• Please read all of the papers and use the template to write your reviews about the two of them. You can edit the template to shorten the title or exceed the 1-page limit a little bit but no longer than 2 pages, please.

[20/02/05]

• Please check the Lectures below for tutorials and lecture slides on Stereo Estimation.
• You can also find the list of papers and the pdf/code/talk related to them.
• Please read all of the papers and use the template to write your reviews about the two of them.

[20/02/03]

• The webpage is up!
  You can find the syllabus, survey, presentations, and the lectures below.
• Please make sure you have a date for the presentation! (by filling the excel sheet that I sent you via email.
• Please start working on the video lectures on Deep Learning using PyTorch!
• Please start working on the Project Proposal!

Information

• Syllabus [pdf]
• Survey [pdf]
• Review Template [zip]
• Presentations

Week	Subject	Presenter#1	Presenter#2
1	Introduction	–	–
2	Depth Estimation	Farzin Negahbani	Onur Keleş
3	Multi-view Reconstruction	Çağan Selim Çoban	Sadra Safadoust
4	Optical Flow Estimation	Milad Jamalzadeh	Can Arda Okçuoğlu
5	Scene Flow Estimation	Cansu Korkmaz	Doğa Can Özil
6	Visual Odometry	Merve Karakaş	Nasrin Rahimi
7	SLAM	Dursun Bekci
8	Localization (Place Recognition)	Onur Berk Töre	Batuhan Yücer
9	2D Object Detection	Gökalp Ünsal	Burak Teke
10	Object Detection Extended	Halil Eralp Koçaş
11	Visual (Single) Object Tracking
12	Multi-Object Tracking	Buğra Can Sefercik
13	Semantic Segmentation	Sadra Safadoust
14	Instance Segmentation	Cenk Burak Egeli
15	End-to-end Driving	Burak Cem Balcı	Ege Onat Özsüer
16	Project Presentations

Lectures

• Introduction [PDF]
• Sensors, Datasets & Benchmarks [PDF]
• Stereo Estimation [PDF]
  • Tutorials:
    • • Video Lectures on 3D Vision [12,13,15]
      • Video Lectures on Graphical Models
  • Papers:
    • • Stereo Processing by Semi-Global Matching and Mutual Information, PAMI 2008 [PDF]
        H. Hirschmueller
      • Continuous Markov Random Fields for Robust Stereo Estimation, ECCV 2012 [PDF] [talk]
        K. Yamaguchi, D. McAllester, and R. Urtasun
      • Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches, CVPR 2015 [PDF] [code]
        J. Zbontar and Y. LeCun
      • GA-Net: Guided Aggregation Net for End-To-End Stereo Matching, CVPR 2019 [PDF] [code]
        F. Zhang, V. Prisacariu, R. Yang, and P. Torr
• Multi-view Reconstruction [PDF]
  • Tutorials:
    • • Multi-View Stereo: A Tutorial
      • Multi-view 3D Reconstruction for Dummies by Jianxiong Xiao
      • Video Lecture on “3D Reconstruction with Deep Learning” by Eduard Ramon at UPC TelecomBCN Barcelona, 2019
      • Tutorial on Large-Scale 3D Modelling at CVPR 2017
  • Papers:
    • • Unsupervised Learning of Depth and Ego-Motion From Video, CVPR 2017 [PDF] [code:tf] [code:PyTorch]
        T. Zhou, M. Brown, N. Snavely, and D. G. Lowe
      • Structure-from-Motion Revisited (COLMAP), CVPR 2016 [PDF] [code]
        J. L. Schonberger and J. M. Frahm
      • MVSNet: Depth Inference for Unstructured Multi-view Stereo, ECCV 2018 [PDF] [code]
        Y. Yao, Z. Luo, L. Shiwei, T. Fang, and L. Quan
• Optical Flow Estimation [PDF]
  • Papers:
    • • (optional) EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow, CVPR 2015 [PDF] [project] [code]
        J. Revaud, P. Weinzaepfel, Z. Harchaoui, and C. Schmid.
      • PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume, CVPR 2018 [PDF] [code] [talk1] [talk2]
        D. Sun, X. Yang, M. Liu, and J. Kautz
      • SelFlow: Self-Supervised Learning of Optical Flow, CVPR 2019 [PDF] [code] [talk]
        P. Liu, M. Lyu, I. King, and J. Xu
        or
        DDFlow: Learning Optical Flow with Unlabeled Data Distillation, AAAI 2019 [PDF] [code]
        P. Liu, I. King, M. Lyu, and J. Xu
• Scene Flow Estimation [PDF]
  • Tutorials:
    • • Lecture on Flow Estimation by Min Bai
      • Low-level Vision for Autonomous Driving by Raquel Urtasun
      • CS231A Course Notes on Epipolar Geometry by Kenji Hata and Silvio Savarese
  •  Papers:
    • • (optional) Robust Monocular Epipolar Flow Estimation, CVPR 2013 [PDF]
        K. Yamaguchi, D. McAllester and R. Urtasun
      • (optional) 3D Scene Flow Estimation with a Piecewise Rigid Scene Model, IJCV 2015 [PDF]
        C. Vogel, K. Schindler, and S. Roth
      • Deep Rigid Instance Scene Flow, CVPR 2019 [PDF]
        N. W. Ma, S. Wang, R. Hu, Y. Xiong, and R. Urtasun
      • PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds, CVPR 2019 [PDF]
        A. Behl, D. Paschalidou, S. Donne, and A. Geiger
• Visual Odometry [PDF]
  • Tutorials:
    • • VO by Davide Scaramuzza Part I, Part II
      • Course Notes by Davide Scramuzza on Vision Algorithms for Mobile Robotics
      • Introduction to VO by Karel Zimmermann
  •  Papers:
    • • Visual-lidar Odometry and Mapping: Low- rift, Robust, and Fast, ICRA 2015 [PDF]
        J. Zhang and S. Singh
      • Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry, ECCV 2018 (oral) [PDF] [talk]
        N. Yang, R. Wang, J. Stueckler, and D. Cremers
      • (optional) D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry, CVPR 2020 [PDF]
        N. Yang, L. Stumberg, R. Wang, and D. Cremers
• SLAM [PDF]
  • Tutorials:
    • • VO by Davide Scaramuzza Part I, Part II
      • Simultaneous Localisation and Mapping (SLAM): Part II
      • Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age

      • Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving

•  Localization [PDF]
  • Tutorials:
    • • A survey on Visual-Based Localization: On the benefit of heterogeneous data
      • ICCV2019 Workshop on Large-Scale Visual Place Recognition and Image-Based Localization
      • Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age
  • Papers:
    • • DSAC – Differentiable RANSAC for Camera Localization, CVPR 2017 [PDF] [code] [project]
        E. Brachmann, A. Krull, S. Nowozin, J. Shotton, F. Michel, S. Gumhold, C. Rother
        
      • Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions, CVPR 2018 [PDF]

        T. Sattler, W. Maddern, C. Toft, A. Torii, L. Hammarstrand, E. Stenborg, D. Safari, M. Okutomi, M. Pollefeys, J. Sivic, F. Kahl, and T. Pajdla
•  Object Detection [PDF]
  • Tutorials:
    • • A curated list of object detectors [link1] [link2]
      • Recent Advances in Deep Learning for Object Detection
      • A Survey of Deep Learning-based Object Detection
      • Object Detection in 20 Years: A Survey
      • Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks
      • Deep Learning for Generic Object Detection: A Survey
      • Imbalance Problems in Object Detection: A Review
  • Papers:
    • • Feature Pyramid Networks for Object Detection, CVPR 2017 [PDF] [code]
        T.-Y. Lin, P. Dollar, R. Girshick, K. He, B. Hariharan, and S. Belongie
        
      • Cornernet: Detecting objects as paired keypoints, ECCV 2018 [PDF] [code]
        H. Law and J. Deng
      • (optional) EfficientDet: Scalable and Efficient Object Detection, ARXIV 2020 [PDF]
        M. Tan, R. Pang, and Q. V. Le

•  Object Detection Extended [PDF1] [PDF2]
  • • Sequence Level Semantics Aggregation for Video Object Detection, ICCV 2019 [PDF] [code]
      H. Pu, Y. Chen, N. Wang, and Z. Zhang
    • Frustum PointNets for 3D Object Detection from RGB-D Data, CVPR 2018 [PDF] [code]
      C. R. Qi, W. Liu, C. Wu, H. Su, and L. J. Guibas

•  Visual Object Tracking [PDF1] [PDF2] [list of VOT]
  • • SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks, CVPR 2019 [PDF] [project]
      B. Li, W. Wu, Q. Wang, F. Zhang, J. Xing, and J. Yan
    • Learning Discriminative Model Prediction for Tracking, ICCV 2019 [PDF] [code]
      G. Bhat, M. Danelljan, L. V. Gool, and R. Timofte
    • Learning Correspondence from the Cycle-Consistency of Time, CVPR 2019 [PDF] [code]
      X. Wang, A. Jabri, and A. A. Efros

•  Mult-Object Tracking [PDF]
  • Tutorials:
    • Video Lecture by L. Leal-Taixe
  •  Papers:
    • Learning a Neural Solver for Multiple Object Tracking, CVPR 2020 [PDF] [code]
      G. Braso and L. Leal-Taixe
    • Tracking without Bells and Whistles, ICCV 2019 [PDF] [code]
      P. Bergmann, T. Meinhardt, and L. Leal-Taixe

•  Semantic Segmentation [PDF]
  •  Papers:
    • Gated-SCNN: Gated Shape CNNs for Semantic Segmentation, ICCV 2019 [PDF] [code]
      T. Takikawa, D. Acuna, V. Jampani, and S. Fidler
    • Object-Contextual Representations for Semantic Segmentation, ARXIV 2019 [PDF] [code]
      Y. Yuan, X. Chen, and J. Wang
      or
    • Deep High-Resolution Representation Learning for Visual Recognition, PAMI 2020 [PDF] [code]
      J. Wang, K. Sun, T. Cheng, B. Jiang, C. Deng, Y. Zhao, D. Liu, Y. Mu, M. Tan, X. Wang, W. Liu, and B. Xiao

•  Instance Segmentation [PDF]
  •  Papers:
    • Video Instance Segmentation, ICCV 2019 [PDF]
      L. Yang, Y. Fan, and N. Xu.
    • PolyTransform: Deep Polygon Transformer for Instance Segmentation, CVPR 2020 [PDF]
      J. Liang, N. Homayounfar, Y.-C. Ma, Y. Xiong, R. Hu, and R. Urtasun.