diff --git a/README.md b/README.md
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@@ -538,27 +538,36 @@ _Deep Learning Methods_
:camera::space_invader: MarrNet: 3D Shape Reconstruction via 2.5D Sketches (2017) [[Paper]](http://marrnet.csail.mit.edu/)

-:game_die: PU-Net: Point Cloud Upsampling Network (2018) [[Paper]](https://arxiv.org/pdf/1801.06761.pdf) [[Code]](https://github.com/yulequan/PU-Net)
-
-
:camera::space_invader::game_die: Learning a Multi-View Stereo Machine (2017 NIPS) [[Paper]](http://bair.berkeley.edu/blog/2017/09/05/unified-3d/)

:space_invader: 3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions (2017) [[Paper]](http://3dmatch.cs.princeton.edu/)

+:space_invader: Scaling CNNs for High Resolution Volumetric Reconstruction from a Single Image (2017) [[Paper]](https://ieeexplore.ieee.org/document/8265323/)
+
+
+:game_die: PU-Net: Point Cloud Upsampling Network (2018) [[Paper]](https://arxiv.org/pdf/1801.06761.pdf) [[Code]](https://github.com/yulequan/PU-Net)
+
+
:camera::space_invader: Multi-view Consistency as Supervisory Signal for Learning Shape and Pose Prediction (2018 CVPR) [[Paper]](https://shubhtuls.github.io/mvcSnP/)

:camera::game_die: Object-Centric Photometric Bundle Adjustment with Deep Shape Prior (2018) [[Paper]](http://ci2cv.net/media/papers/WACV18.pdf)

-:camera::game_die: Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction (AAAI 2018) [[Paper]](https://chenhsuanlin.bitbucket.io/3D-point-cloud-generation/)
+:camera::game_die: Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction (2018 AAAI) [[Paper]](https://chenhsuanlin.bitbucket.io/3D-point-cloud-generation/)

:gem: Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images (2018) [[Paper]](http://bigvid.fudan.edu.cn/pixel2mesh/)

+:gem: AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation (2018 CVPR) [[Paper]](http://imagine.enpc.fr/~groueixt/atlasnet/) [[Code]](https://github.com/ThibaultGROUEIX/AtlasNet)
+
+
+:space_invader::gem: Deep Marching Cubes: Learning Explicit Surface Representations (2018 CVPR) [[Paper]](http://www.cvlibs.net/publications/Liao2018CVPR.pdf)
+
+
## Style Transfer
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