Difference between revisions of "ReadingGroup"

From Deep Depth 116E167 Project Documentation
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= Proposed Schedule =
 
= Proposed Schedule =
  
* Week of 11 Sept: Foley & Maitlin Chapter 6 - Distance & Size Perception
+
* Week of 11 Sept: Foley & Maitlin Chapter 6: Distance & Size Perception
 
* Week of 18 Sept: Saxena, Min & Ng: Make3D
 
* Week of 18 Sept: Saxena, Min & Ng: Make3D
 
* Week of 25 Sept: Michels, Saxena & Ng: High speed obstacle avoidance
 
* Week of 25 Sept: Michels, Saxena & Ng: High speed obstacle avoidance
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* Week of 06 Novr: Eigen, Puhrsch & Fergus: Depth map prediction
 
* Week of 06 Novr: Eigen, Puhrsch & Fergus: Depth map prediction
 
* Week of 13 Novr: Shelhamer, Long & Darrell: Fully Convolutional Segmentation
 
* Week of 13 Novr: Shelhamer, Long & Darrell: Fully Convolutional Segmentation
* Week of 20 Novr:  
+
* Week of 20 Novr: He, Zhang, Ren & Sun: ResNet
* Week of 27 Novr:  
+
* Week of 27 Novr: Girshick, Donahue, Darrell & Malik: R-CNN
* Week of 04 Decr:  
+
* Week of 04 Decr: Liao, Huang, Wang, Kodagoda, Yu & Liu: Fuse with laser
* Week of 11 Decr:  
+
* Week of 11 Decr: Giuisti et al.: Forest trails CNN
* Week of 18 Decr:  
+
* 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 =
 
= Details =
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https://books.google.com.tr/books?id=jLBmCgAAQBAJ&printsec=frontcover
 
https://books.google.com.tr/books?id=jLBmCgAAQBAJ&printsec=frontcover
 +
Go to Chapter 6.
  
 
== Saxena, Min & Ng: Make3D ==
 
== Saxena, Min & Ng: Make3D ==
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http://arxiv.org/abs/1605.06211
 
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
 +
 +
== Li, Klein & Yao: Fully convolutional depth 3 ==
 +
 +
http://arxiv.org/abs/1607.00730

Revision as of 18:16, 15 August 2017

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: Midterm 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

https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf

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

Li, Klein & Yao: Fully convolutional depth 3

http://arxiv.org/abs/1607.00730