MLSS - Slides, Notes and References

Slides

Talk 1: Sensors, Localization and Control
Talk 2: Classification, Detection and Regression
Talk 3: Weather, Regression and Speculation

Notes

The new computer vision (D.A. Forsyth) very early draft of new book, with lots of info on cameras, calibration, simple network ideas, and registration

Some reading materials

Point set registration
- Weighted least squares solutions for rotation translation; very nice notes from Olga Sorkine-Hornung and Michael Rabinovitch
- Notes on robustness and iteratively reweighted least squares
- Robust registration of point sets using iteratively reweighted least squares P. Bergstrom and A.Edlund, Computational Optimization and Applications July 2014, Volume 58, Issue 3, pp 543–561 (click from inside UIUC intranet!)
- Geometrically Stable Sampling for the ICP AlgorithmN. Gelfand; L. Ikemoto; S. Rusinkiewicz; M. Levoy, (3DIMPVT) 2003
- Efficient Variants of the ICP AlgorithmS.Rusinkiewicz and M. Levoy, (3DIMPVT), 2001
- Translation Synchronization via Truncated Least SquaresX Huang, Z Liang, C. Bajaj, Q. Huang, NeurIPS17
- Uncertainty quantification for multi-scan registration X Huang, Z Liang, Q Huang ACM Transactions on Graphics (TOG) 39 (4), 130: 1-130: 24
- Multiple View Geometry in Computer Vision Second Edition Richard Hartley and Andrew Zisserman, Cambridge University Press, March 2004.
- Visual odometry Stephan Weiss
- Stereo Visual odometryChris Beall
- Dense odometryRichard Newcombe
- SuperPoint: Self-Supervised Interest Point Detection and Description DeTone, Malisciewicz, Rabinovich, 2018
- An implementation of SuperPoint
- Tutorial on visual slam at CVPR2014
  I found the following particularly helpful
  - Visual odometry Stephan Weiss
  - Stereo Visual odometryChris Beall
  - Dense odometryRichard Newcombe
- Great notes on EKF-SLAM by Joan Sola, with Matlab code, etc
- Christian Forster, Zichao Zhang, Michael Gassner, Manuel Werlberger, Davide Scaramuzza SVO: Semi-Direct Visual Odometry for Monocular and Multi-Camera Systems IEEE Transactions on Robotics, Vol. 33, Issue 2, pages 249-265, Apr. 2017.
- Dense visual slam an earlier version of lsd-slam for RGB-D cameras, code too
- Dense Visual SLAM for RGB-D Cameras (C. Kerl, J. Sturm and D. Cremers), In Proc. of the Int. Conf. on Intelligent Robot Systems (IROS), 2013.
My slides on higher dimensional motion planning
My slides on planning in the presence of dynamics, with a bit of stuff about motion graphs
Notes on sampling based motion planning, chapter 5 of Lavalle's book "Planning Algorithms"
Notes on planning in the presence of dynamics , chapter 14 of Lavalle's book "Planning Algorithms"
Dubins, L.E. (July 1957). "On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents". American Journal of Mathematics. 79 (3): 497–516.
J. A. Reeds and L. A. Shepp. Optimal paths for a car that goes both forwards and backwards. Pacific Journal of Mathematics, 145(2):367-393, 1990.
The open mpl library and app
Very nice CMU motion planning slides, I believe by H. Choset
US Patent 9081385 (lane boundaries)
Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection Lucas Tabelini, Rodrigo Berriel, Thiago M. Paixão, Claudine Badue, Alberto F. De Souza, Thiago Oliveira-Santos Code
Off-road Path Following using Region Classification and Geometric Projection Constraints Y. Alon; A. Ferencz; A. Shashua, CVPR 06
Detection and tracking of boundary of unmarked roads Young-Woo Seo; Ragunathan Raj Rajkumar, 17'th international conf on information fusion, 2014
Geometric Constrained Joint Lane Segmentation and Lane Boundary Detection Jie Zhang, Yi Xu, Bingbing Ni, Zhenyu Duan; Proceedings of the European Conference on Computer Vision (ECCV), 2018, pp. 486-502
Lane detection using lane boundary marker network with road geometry constraints Hussam Ullah Khan, Afsheen Rafaqat Ali, Ali Hassan, Ahmed Ali, Wajahat Kazmi, Aamer Zaheer; Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2020, pp. 1834-1843
Robust Lane Detection from Continuous Driving Scenes Using Deep Neural Networks Qin Zou, Hanwen Jiang, Qiyu Dai, Yuanhao Yue, Long Chen, Qian Wang
Horizon detection page by Nathan Jacobs, including horizon data and some nice papers on horizon detection.
Urban 3D Semantic Modelling Using Stereo Vision Sunando Sengupta Eric Greveson, Ali Shahrokni2 Philip H. S. Torr, ICRA, 2013
FAST SEMANTIC SEGMENTATION OF 3D POINT CLOUDS WITH STRONGLY VARYING DENSITY Timo Hackel, Jan D. Wegner, Konrad Schindler
"Fully Convolutional Networks for Semantic Segmentation" Jonathan Long∗ Evan Shelhamer∗ Trevor Darrell, 2014
The Stixel world: A medium-level representation of traffic scenes Marius Cordts, et al., ArXiv, 2017
Towards a Global Optimal Multi-Layer Stixel Representation of Dense 3D Data David Pfeiffer, Uwe Franke, BMVC 2011
3D Traffic Scene Understanding from Movable Platforms. Andreas Geiger. Martin Lauer. Christian Wojek. Christoph Stiller. Raquel Urtasun
Learning to Look around Objects for Top-View Representations of Outdoor Scenes Samuel Schulter, Menghua Zhai, Nathan Jacobs, Manmohan Chandraker
A Parametric Top-View Representation of Complex Road Scenes Ziyan Wang, Buyu Liu, Samuel Schulter, Manmohan Chandraker
Efficient reductions for imitation learning Ross and Bagnell, AIStats, 10 (problems with imitation learning exposed)
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning Ross, Gordon and Bagnell, AIStats-11, (Dagger)
ALVINN: an autonomous land vehicle in a neural network Dean Pomerlau, NIPS, 1989 (early - first?- autonomous driver)
3D Traffic Scene Understanding from Movable Platforms. Andreas Geiger. Martin Lauer. Christian Wojek. Christoph Stiller. Raquel Urtasun
Learning to Look around Objects for Top-View Representations of Outdoor Scenes Samuel Schulter, Menghua Zhai, Nathan Jacobs, Manmohan Chandraker
A Parametric Top-View Representation of Complex Road Scenes Ziyan Wang, Buyu Liu, Samuel Schulter, Manmohan Chandraker
Great general reading with super pix Color and Light in Nature, David K. Lynch, William Livingston, Cambridge University Press, Jun 29, 1995
More great general readingLight and Color in the Outdoors by Marcel Minnaert (Author), L. Seymour (Translator), Springer, 1995

Haze and dehazing

Vision in bad weather S.K. Nayar and S. Narasimhan, ICCV 1995
Single image dehazing Raanan Fattal, SIGGRAPH 08
DehazeNet: An End-to-End System for Single Image Haze Removal Bolun Cai, Xiangmin Xu, Kui Jia, Chunmei Qing, Dacheng Tao, 2016
FFA-Net: Feature Fusion Attention Network for Single Image Dehazing Xu Qin, Zhilin Wang, Yuanchao Bai, Xiaodong Xie, Huizhu Jia
FD-GAN: Generative Adversarial Networks with Fusion-discriminator for Single Image Dehazing Yu Dong, Yihao Liu, He Zhang, Shifeng Chen, Yu Qiao
Implicit Euler ODE Networks for Single-Image Dehazing Jiawei Shen, Zhuoyan Li, Lei Yu, Gui-Song Xia, Wen Yang CVPR 20 workshops
ACDC: The Adverse Conditions Dataset with Correspondences for Semantic Driving Scene Understanding Christos Sakaridis, Dengxin Dai, Luc Van Gool

Lidar and haze

LIBRE: The Multiple 3D LiDAR Dataset Alexander Carballo, Jacob Lambert, Abraham Monrroy-Cano, David Robert Wong, Patiphon Narksri, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda
Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather Martin Hahner, Christos Sakaridis, Dengxin Dai, Luc Van Gool
Pointillism: accurate 3D bounding box estimation with multi-radars Kshitiz Bansal, Keshav Rungta,Siyuan Zhu,Dinesh Bharadia
Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather Mario Bijelic, Tobias Gruber, Fahim Mannan, Florian Kraus, Werner Ritter, Klaus Dietmayer, Felix Heide

Rain effects

Object Detection Under Rainy Conditions for Autonomous Vehicles: A Review of State-of-the-Art and Emerging Techniques Mazin Hnewa, Hayder Radha, 2021
Vision and Rain K. Garg and S.K. Nayar International Journal of Computer Vision volume 75, pages3–27(2007)
Programmable Automotive Headlights Robert Tamburo, Eriko Nurvitadhi, Abhishek Chugh, Mei Chen, Anthony Rowe, Takeo Kanade, Srinivasa G. Narasimhan

Rain simulation

Rain rendering for evaluating and improving robustness to bad weather Maxime Tremblay, Shirsendu Sukanta Halder, Raoul de Charette, Jean-François Lalonde

Rain removal

Restoring An Image Taken Through a Window Covered with Dirt or Rain David Eigen Dilip Krishnan Rob Fergus, ICCV 13
Depth-attentional Features for Single-image Rain Removal Xiaowei Hu, Chi-Wing Fu, Lei Zhu2 and Pheng-Ann Heng, CVPR 2019
Rain Streak Removal Using Layer Priors Yu Li, Robby T. Tan, Xiaojie Guo, Jiangbo Lu, Michael S. Brown, CVPR 16
Semi-supervised Transfer Learning for Image Rain Removal Wei Wei, Deyu Meng, Qian Zhao, Zongben Xu, Ying Wu, CVPR 19
Deep Joint Rain Detection and Removal from a Single Image Wenhan Yang, Robby T. Tan, Jiashi Feng, Jiaying Liu, Zongming Guo, and Shuicheng Yan, CVPR 17