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Added code to the paper Global-to-Local Generative Model for 3D Shapes

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@ -697,7 +697,7 @@ _Deep Learning Methods_
:space_invader: <b>Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers (2018 CVPR)</b> [[Paper]](https://arxiv.org/pdf/1804.10975.pdf)
<p align="center"><img width="50%" src="https://github.com/timzhang642/3D-Machine-Learning/blob/master/imgs/Matryoshka%20Networks-%20Predicting%203D%20Geometry%20via%20Nested%20Shape%20Layers%20(2018%20CVPR).jpeg" /></p>
:space_invader: <b>Global-to-Local Generative Model for 3D Shapes (SIGGRAPH Asia 2018)</b> [[Paper]](http://vcc.szu.edu.cn/research/2018/G2L)
:space_invader: <b>Global-to-Local Generative Model for 3D Shapes (SIGGRAPH Asia 2018)</b> [[Paper]](http://vcc.szu.edu.cn/research/2018/G2L)[[Code]](https://github.com/Hao-HUST/G2LGAN)
<p align="center"><img width="50%" src="https://github.com/timzhang642/3D-Machine-Learning/blob/master/imgs/Global-to-Local%20Generative%20Model%20for%203D%20Shapes.jpg" /></p>
:gem::game_die::space_invader: <b>ALIGNet: Partial-Shape Agnostic Alignment via Unsupervised Learning (TOG 2018)</b> [[Paper]](https://bit.ly/alignet) [[Code]](https://github.com/ranahanocka/ALIGNet/)