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Title: GitHub - unMajorce/3D-Machine-Learning: A resource repository for 3D machine learning

Open Graph Title: GitHub - unMajorce/3D-Machine-Learning: A resource repository for 3D machine learning

X Title: GitHub - unMajorce/3D-Machine-Learning: A resource repository for 3D machine learning

Description: A resource repository for 3D machine learning. Contribute to unMajorce/3D-Machine-Learning development by creating an account on GitHub.

Open Graph Description: A resource repository for 3D machine learning. Contribute to unMajorce/3D-Machine-Learning development by creating an account on GitHub.

X Description: A resource repository for 3D machine learning. Contribute to unMajorce/3D-Machine-Learning development by creating an account on GitHub.

Opengraph URL: https://github.com/unMajorce/3D-Machine-Learning

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	https://patch-diff.githubusercontent.com/unMajorce/3D-Machine-Learning#table-of-contents
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	https://patch-diff.githubusercontent.com/unMajorce/3D-Machine-Learning#available-courses
UCSD CSE291-I00: Machine Learning for 3D Data (Winter 2018)	https://cse291-i.github.io/index.html
Stanford CS468: Machine Learning for 3D Data (Spring 2017)	http://graphics.stanford.edu/courses/cs468-17-spring/
MIT 6.838: Shape Analysis (Spring 2017)	http://groups.csail.mit.edu/gdpgroup/6838_spring_2017.html
Princeton COS 526: Advanced Computer Graphics (Fall 2010)	https://www.cs.princeton.edu/courses/archive/fall10/cos526/syllabus.php
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[Link]	http://ai2thor.allenai.org/
	https://github.com/timzhang642/3D-Machine-Learning/blob/master/imgs/AI2-Thor.jpeg
[Link]	http://unrealcv.org/
[Paper]	http://www.idm.pku.edu.cn/staff/wangyizhou/papers/ACMMM2017_UnrealCV.pdf
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[Paper]	https://shapenet.cs.stanford.edu/projects/RenderForCNN/
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[Paper]	https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Kendall_PoseNet_A_Convolutional_ICCV_2015_paper.pdf
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[Paper]	https://arxiv.org/pdf/1509.05909.pdf
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[Paper]	https://link.springer.com/article/10.1007/s41095-016-0067-z
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[Paper]	https://arxiv.org/pdf/1704.00390.pdf
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[Paper]	http://3drepresentation.stanford.edu/
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[Paper]	https://arxiv.org/pdf/1612.00496.pdf
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[Paper]	https://www.seas.upenn.edu/~pavlakos/projects/object3d/
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[Paper]	https://arxiv.org/pdf/1702.01381.pdf
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[Paper]	http://3dmatch.cs.princeton.edu/
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[Paper]	http://3dinterpreter.csail.mit.edu/
[Code]	https://github.com/jiajunwu/3dinn
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[Paper]	https://shubhtuls.github.io/mvcSnP/
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[Paper]	http://3dshapenets.cs.princeton.edu/
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[Paper]	http://www.dimatura.net/publications/voxnet_maturana_scherer_iros15.pdf
[Code]	https://github.com/dimatura/voxnet
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[Paper]	http://vis-www.cs.umass.edu/mvcnn/
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[Paper]	https://stanford.edu/~rezab/papers/fusionnet.pdf
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[Paper]	https://arxiv.org/pdf/1604.03265.pdf
[Code]	https://github.com/charlesq34/3dcnn.torch
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[Paper]	https://arxiv.org/pdf/1608.04236.pdf
[Code]	https://github.com/ajbrock/Generative-and-Discriminative-Voxel-Modeling
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[Link]	https://arxiv.org/pdf/1611.08402.pdf
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[Paper]	https://arxiv.org/pdf/1610.07584.pdf
[Code]	https://github.com/zck119/3dgan-release
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[Paper]	https://github.com/ajbrock/Generative-and-Discriminative-Voxel-Modeling
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[Paper]	http://yangyanli.github.io/FPNN/
[Code]	https://github.com/yangyanli/FPNN
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[Paper]	https://arxiv.org/pdf/1611.05009.pdf
[Code]	https://github.com/griegler/octnet
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[Paper]	http://wang-ps.github.io/O-CNN
[Code]	https://github.com/Microsoft/O-CNN
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[Paper]	https://lmb.informatik.uni-freiburg.de/Publications/2017/SZB17a/
[Code]	https://github.com/lmb-freiburg/orion
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[Paper]	http://stanford.edu/~rqi/pointnet/
[Code]	https://github.com/charlesq34/pointnet
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[Paper]	https://arxiv.org/pdf/1706.02413.pdf
[Code]	https://github.com/charlesq34/pointnet2
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[Paper]	http://feedbacknet.stanford.edu/
[Code]	https://github.com/amir32002/feedback-networks
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[Paper]	http://www.arxiv.org/pdf/1704.01222.pdf
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[Paper]	https://arxiv.org/pdf/1801.07829.pdf
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[Paper]	https://yangyanli.github.io/PointCNN/
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[Paper]	http://slidingshapes.cs.princeton.edu/
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[Paper]	https://stanford.edu/class/ee367/Winter2016/Qi_Report.pdf
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[Paper]	http://dss.cs.princeton.edu/
[Code]	https://github.com/shurans/DeepSlidingShape
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[Paper]	http://deepcontext.cs.princeton.edu/
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[Paper]	http://rgbd.cs.princeton.edu/
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[Paper]	https://arxiv.org/pdf/1711.06396.pdf
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[Paper]	https://arxiv.org/pdf/1711.08488.pdf
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[Paper]	https://people.cs.umass.edu/~kalo/papers/LabelMeshes/LabelMeshes.pdf
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[Paper]	https://www.cs.utexas.edu/~huangqx/modeling_sig15.pdf
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[Paper]	http://people.cs.umass.edu/~kalo/papers/shapepfcn/
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[Paper]	http://cs.stanford.edu/~ericyi/project_page/hier_seg/index.html
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[Paper]	https://arxiv.org/pdf/1702.04405.pdf
[Code]	https://github.com/scannet/scannet
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[Paper]	http://stanford.edu/~rqi/pointnet/
[Code]	https://github.com/charlesq34/pointnet
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[Paper]	https://arxiv.org/pdf/1706.02413.pdf
[Code]	https://github.com/charlesq34/pointnet2
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[Paper]	http://www.cs.toronto.edu/~rjliao/papers/iccv_2017_3DGNN.pdf
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[Paper]	https://arxiv.org/pdf/1707.06783.pdf
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[Paper]	https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-4-W4/101/2017/isprs-annals-IV-4-W4-101-2017.pdf
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[Paper]	https://arxiv.org/pdf/1710.07563.pdf
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[Paper]	https://arxiv.org/pdf/1710.06104.pdf
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[Paper]	https://arxiv.org/pdf/1801.07829.pdf
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[Paper]	https://yangyanli.github.io/PointCNN/
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[Paper]	https://arxiv.org/pdf/1803.10409.pdf
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[Paper]	https://arxiv.org/pdf/1712.10215.pdf
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[Paper]	https://arxiv.org/pdf/1802.08275.pdf
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	https://patch-diff.githubusercontent.com/unMajorce/3D-Machine-Learning#3d-model-synthesisreconstruction
[Paper]	http://gravis.dmi.unibas.ch/publications/Sigg99/morphmod2.pdf
[Code]	https://github.com/MichaelMure/3DMM
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[Paper]	http://grail.cs.washington.edu/projects/digital-human/pub/allen03space-submit.pdf
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[Paper]	http://kevinkaixu.net/projects/grass.html
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[Paper]	https://arxiv.org/pdf/1708.01648.pdf
[code]	https://github.com/zouchuhang/3D-PRNN
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[Paper]	http://hiroharu-kato.com/projects_en/neural_renderer.html
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[Paper]	https://arxiv.org/pdf/1710.06104.pdf
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[Code]	https://github.com/maxorange/pix2vox
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[Paper]	https://arxiv.org/pdf/1707.08390.pdf
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[Paper]	http://people.cs.umass.edu/~zlun/papers/StyleSimilarity/StyleSimilarity.pdf
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[Paper]	https://arxiv.org/pdf/1710.09490.pdf
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[Paper]	http://www.cse.wustl.edu/~chenliu/floorplan-transformation.html
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	https://github.com/timzhang642/3D-Machine-Learning/blob/master/imgs/A%20Coarse-to-Fine%20Indoor%20Layout%20Estimation%20(CFILE)%20Method%20(2016).png
[Paper]	http://deeplayout.stanford.edu/
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[Paper]	http://buildingparser.stanford.edu/method.html
[Code]	https://github.com/alexsax/2D-3D-Semantics
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[Paper]	http://3dinterpreter.csail.mit.edu/
[Code]	https://github.com/jiajunwu/3dinn
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[Paper]	http://3dvision.princeton.edu/projects/2016/PBRS/
[Code]	https://github.com/yindaz/pbrs
[Code]	https://github.com/yindaz/surface_normal
[Code]	https://github.com/fyu/dilation
[Code]	https://github.com/s9xie/hed
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[Paper]	https://arxiv.org/pdf/1703.06241.pdf
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[Paper]	http://sscnet.cs.princeton.edu/
[Code]	https://github.com/shurans/sscnet
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[Paper]	https://arxiv.org/pdf/1712.01812.pdf
[Code]	https://shubhtuls.github.io/factored3d/
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[Paper]	https://arxiv.org/pdf/1803.08999.pdf
[Code]	https://github.com/zouchuhang/LayoutNet
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[Paper]	http://art-programmer.github.io/planenet/paper.pdf
[Code]	http://art-programmer.github.io/planenet.html
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