ReadingGroup
From Deep Depth 116E167 Project Documentation
Revision as of 18:16, 15 August 2017 by Damienjadeduff (talk | contribs)
Contents
- 1 Proposed Schedule
- 2 Details
- 2.1 Foley & Maitlin Chapter 6 - Distance & Size Perception
- 2.2 Saxena, Min & Ng: Make3D
- 2.3 Michels, Saxena & Ng: High speed obstacle avoidance
- 2.4 Karsch, Liu & Kang: Depth Transfer
- 2.5 LeCun, Bottou, Bengio & Haffner: CNNs
- 2.6 Krizhevsky, Sutskever & Hinton: ImageNet/AlexNet
- 2.7 Simonyan & Zisserman: VGG-16
- 2.8 Eigen, Puhrsch & Fergus: Depth map prediction
- 2.9 Shelhamer, Long & Darrell: Fully Convolutional Segmentation
- 2.10 He, Zhang, Ren & Sun: ResNets
- 2.11 Girshick, Donahue, Darrell & Malik: R-CNN
- 2.12 Giuisti et al.: Forest trails CNN
- 2.13 Cao, Wu & Shen: Fully convolutional depth 1
- 2.14 Laina et al.: Fully convolutional depth 2
- 2.15 Li, Klein & Yao: Fully convolutional depth 3
Proposed Schedule
- Week of 11 Sept: Foley & Maitlin Chapter 6: Distance & Size Perception
- Week of 18 Sept: Saxena, Min & Ng: Make3D
- Week of 25 Sept: Michels, Saxena & Ng: High speed obstacle avoidance
- Week of 02 Octr: Karsch, Liu & Kang: Depth Transfer
- Week of 09 Octr: LeCun, Bottou, Bengio & Haffner: CNNs
- Week of 16 Octr: Krizhevsky, Sutskever & Hinton: ImageNet/AlexNet
- Week of 23 Octr: Simonyan & Zisserman: VGG-16
- Week of 30 Octr: Break.
- Week of 06 Novr: Eigen, Puhrsch & Fergus: Depth map prediction
- Week of 13 Novr: Shelhamer, Long & Darrell: Fully Convolutional Segmentation
- Week of 20 Novr: He, Zhang, Ren & Sun: ResNet
- Week of 27 Novr: Girshick, Donahue, Darrell & Malik: R-CNN
- Week of 04 Decr: Liao, Huang, Wang, Kodagoda, Yu & Liu: Fuse with laser
- Week of 11 Decr: Giuisti et al.: Forest trails CNN
- Week of 18 Decr: Cao, Wu & Shen: Fully convolutional depth 1
- Week of 25 Decr: Laina et al.: Fully convolutional depth 2
- Week of 01 Jany: Li, Klein & Yao: Fully convolutional depth 3
Details
Foley & Maitlin Chapter 6 - Distance & Size Perception
https://books.google.com.tr/books?id=jLBmCgAAQBAJ&printsec=frontcover Go to Chapter 6.
Saxena, Min & Ng: Make3D
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4531745
Michels, Saxena & Ng: High speed obstacle avoidance
http://dl.acm.org/citation.cfm?id=1102426
Karsch, Liu & Kang: Depth Transfer
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5551153 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6787109
LeCun, Bottou, Bengio & Haffner: CNNs
http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf
Krizhevsky, Sutskever & Hinton: ImageNet/AlexNet
Simonyan & Zisserman: VGG-16
http://arxiv.org/abs/1409.1556
Eigen, Puhrsch & Fergus: Depth map prediction
https://www.cs.nyu.edu/~deigen/depth/
Shelhamer, Long & Darrell: Fully Convolutional Segmentation
http://arxiv.org/abs/1605.06211
He, Zhang, Ren & Sun: ResNets
https://arxiv.org/abs/1512.03385
Girshick, Donahue, Darrell & Malik: R-CNN
https://arxiv.org/abs/1311.2524
Giuisti et al.: Forest trails CNN
http://ieeexplore.ieee.org/document/7358076/
See also youtube.
Cao, Wu & Shen: Fully convolutional depth 1
http://arxiv.org/abs/1605.02305
Laina et al.: Fully convolutional depth 2
http://arxiv.org/abs/1606.00373