Lecture Schedule
From cs331b Special Topics in 3dRR
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| Large scale 3D reconstruction by structure from motion : | | Large scale 3D reconstruction by structure from motion : | ||
- | *Sameer Agarwal, Yasutaka Furukawa, Noah Snavely, Ian Simon, Brian Curless, Steven M. Seitz and Richard Szeliski Communications of the ACM, Vol. 54, No. 10, Pages 105-112, October 2011 [http:// | + | *Sameer Agarwal, Yasutaka Furukawa, Noah Snavely, Ian Simon, Brian Curless, Steven M. Seitz and Richard Szeliski Communications of the ACM, Vol. 54, No. 10, Pages 105-112, October 2011 [http://grail.cs.washington.edu/projects/rome/rome_paper.pdf link] |
*Jan-Michael Frahm, Pierre Georgel, David Gallup, Tim Johnson, Rahul Raguram, Changchang Wu, Yi-Hung Jen, Enrique Dunn, Brian Clipp, Svetlana Lazebnik, Marc Pollefeys, ECCV 2010 | *Jan-Michael Frahm, Pierre Georgel, David Gallup, Tim Johnson, Rahul Raguram, Changchang Wu, Yi-Hung Jen, Enrique Dunn, Brian Clipp, Svetlana Lazebnik, Marc Pollefeys, ECCV 2010 | ||
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| Indoor scene layout reconstruction: | | Indoor scene layout reconstruction: | ||
- | *David Lee, Takeo Kanadem Matrial Hebert. "3D Scene Analysis". CVPR2009 | + | *David Lee, Takeo Kanadem Matrial Hebert. "3D Scene Analysis". CVPR2009 [http://www.cs.cmu.edu/~dclee/pub/cvpr09lee.pdf link] |
*A. Schwing and R. Urtasun, Efficient Exact Inference for 3D Indoor Scene Understanding In European Conference on Computer Vision (ECCV), Florence, Italy, October 2012 | *A. Schwing and R. Urtasun, Efficient Exact Inference for 3D Indoor Scene Understanding In European Conference on Computer Vision (ECCV), Florence, Italy, October 2012 | ||
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| <span style="color: rgb(255, 0, 0);">'''10/17''' | | <span style="color: rgb(255, 0, 0);">'''10/17''' | ||
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| <span style="color: rgb(255, 0, 0);">'''11/5''' | | <span style="color: rgb(255, 0, 0);">'''11/5''' | ||
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Revision as of 00:20, 26 September 2013
Lect. | Date | Topics | Presenter | Paper/Slides |
---|---|---|---|---|
1 | 9/23 | Introductions | slides | |
2 | 9/25 | Representing and Recognizing Objects | Guest lecturer: Y. Xiang |
3D object recognition by aspect graph-based models:
|
3 | 9 /30 | Representing and Recognizing Objects | 3D detection from D-RGB data:
| |
4 | 10/2 | Representing and Recognizing Objects | Guest lecturer: Dr. M. Stark | 3D object recognition by deformable part models:
|
5 | 10/7 | Representing the 3D Space | Large scale 3D reconstruction by structure from motion :
| |
6 | 10/9 | Representing the 3D Space | Indoor scene layout reconstruction:
| |
7 | 10/14 | Understanding Complex Scenes | Joint 3D reconstruction and object detection:
| |
8 | 10/16 | Understanding Complex Scenes | Guest lecturer: B. Kim | 2D/3D CRF models fo understanding:
|
10/17
| Project Proposal due | |||
9 | 10/21 | Understanding Complex Scenes | Guest lecturer: Y. Bao | Semantic structure from motion:
|
10 | 10/23 | Understanding Complex Scenes | Tutorial on MCMC:
| |
11 | 10/28 | Understanding Complex Scenes | Joint segmentation and reconstruction from D-RGB data (I):
| |
12 | 10/30 | Understanding Complex Scenes | Joint segmentation and reconstruction from D-RGB data (II):
| |
13 | 11/4 | Understanding Human Pose | Guest lecturer: Dr. Roland Angst | Joint segmentation and reconstruction from D-RGB data (III):
|
11/5
| Project Mid-term Report due | |||
14 | 11/6 | Understanding Human Pose | Human pose estimation and activity recognition from 2D
images:
| |
15 | tba | Understanding Human Activities | Human pose estimation and activity recognition from D-RGB
data:
| |
16 | 11/11 | Understanding Human Activities | Guest lecturer: Dr. W. Choi | Recognizing collective activities:
|
17 | 11/13 | Understanding Human Activities |
| |
18 | tba | Understanding Human Activities | Joint estimation of object/scene affordances and human
pose:
| |
19 | 11/18 | Final Project Presentations | ||
20 | 11/20 | Final Project Presentations | ||
| 11/25 | no class - Thanksgiving Break | ||
| 11/27 | no class - Thanksgiving Break | ||
| 12/2 |
no class due to ICCV | ||
| 12/4 | no class due to ICCV | ||
| 12/13 | Final Project Report Due | ||
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