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
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:
- 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
- Stereo Processing by Semi-Global Matching and Mutual Information, PAMI 2008 [PDF]
-
- Multi-view Reconstruction [PDF]
- Tutorials:
- 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
- Unsupervised Learning of Depth and Ego-Motion From Video, CVPR 2017 [PDF] [code:tf] [code:PyTorch]
-
- 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
- (optional) EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow, CVPR 2015 [PDF] [project] [code]
-
- Papers:
- Scene Flow Estimation [PDF]
- Tutorials:
- 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
- (optional) Robust Monocular Epipolar Flow Estimation, CVPR 2013 [PDF]
-
- Visual Odometry [PDF]
- Tutorials:
- 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
- Visual-lidar Odometry and Mapping: Low- rift, Robust, and Fast, ICRA 2015 [PDF]
-
- SLAM [PDF]
- Localization [PDF]
- Tutorials:
- 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
- DSAC – Differentiable RANSAC for Camera Localization, CVPR 2017 [PDF] [code] [project]
-
- 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
- Feature Pyramid Networks for Object Detection, CVPR 2017 [PDF] [code]
-
- Tutorials:
- 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
- SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks, CVPR 2019 [PDF] [project]
-
- Mult-Object Tracking [PDF]
- Tutorials:
- Papers:
- 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
- Gated-SCNN: Gated Shape CNNs for Semantic Segmentation, ICCV 2019 [PDF] [code]
- Papers: