From 45aa6a6a80f4fbc8cda44168904d2c4143b7e650 Mon Sep 17 00:00:00 2001 From: "Yuxuan (Tim) Zhang" Date: Sun, 29 Oct 2017 19:38:58 -0400 Subject: [PATCH] Update README.md --- README.md | 32 ++++++++++++++++++++++++++++++++ 1 file changed, 32 insertions(+) diff --git a/README.md b/README.md index b3fb147..7968cf6 100644 --- a/README.md +++ b/README.md @@ -20,6 +20,8 @@ To make it a collaborative project, you may add content throught pull requests o [Princeton CS597: Geometric Modeling and Analysis (Fall 2003)](https://www.cs.princeton.edu/courses/archive/fall03/cs597D/) +[Geometric Deep Learning](http://geometricdeeplearning.com/) + ## Datasets To see a survey of RGBD datasets, I recommend to check out Michael Firman's [collection](http://www0.cs.ucl.ac.uk/staff/M.Firman//RGBDdatasets/) as well as the associated paper, [RGBD Datasets: Past, Present and Future](https://arxiv.org/pdf/1604.00999.pdf). Point Cloud Library also has a good dataset [catalogue](http://pointclouds.org/media/). @@ -48,6 +50,9 @@ To see a survey of RGBD datasets, I recommend to check out Michael Firman's [col :space_invader: 3D GAN: Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling (2016) [[Paper]](https://arxiv.org/pdf/1610.07584.pdf)

+:space_invader: Generative and Discriminative Voxel Modeling with Convolutional Neural Networks (2017) [[Paper]](https://github.com/ajbrock/Generative-and-Discriminative-Voxel-Modeling) +

+ :space_invader: FPNN: Field Probing Neural Networks for 3D Data (2016) [[Paper]](http://yangyanli.github.io/FPNN/)

@@ -159,6 +164,9 @@ _Deep Learning Methods_ :camera: Learning to Generate Chairs, Tables and Cars with Convolutional Networks (2014) [[Paper]](https://arxiv.org/pdf/1411.5928.pdf)

+:camera: Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis (2015, NIPS) [[Paper]](https://papers.nips.cc/paper/5639-weakly-supervised-disentangling-with-recurrent-transformations-for-3d-view-synthesis.pdf) +

+ :game_die: Analysis and synthesis of 3D shape families via deep-learned generative models of surfaces (2015) [[Paper]](https://people.cs.umass.edu/~hbhuang/publications/bsm/)

@@ -189,6 +197,9 @@ _Deep Learning Methods_ :camera: Unsupervised Learning of 3D Structure from Images (2016) [[Paper]](https://arxiv.org/pdf/1607.00662.pdf)

+:space_invader: Generative and Discriminative Voxel Modeling with Convolutional Neural Networks (2016) [[Paper]](https://arxiv.org/pdf/1608.04236.pdf) [[Code]](https://github.com/ajbrock/Generative-and-Discriminative-Voxel-Modeling) +

+ :camera: Multi-view Supervision for Single-view Reconstruction via Differentiable Ray Consistency (2017) [[Paper]](https://shubhtuls.github.io/drc/)

@@ -198,15 +209,36 @@ _Deep Learning Methods_ :space_invader: Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs (2017) [[Paper]](https://arxiv.org/pdf/1703.09438.pdf)

+:space_invader: Hierarchical Surface Prediction for 3D Object Reconstruction (2017) [[Paper]](https://arxiv.org/pdf/1704.00710.pdf) +

+ :game_die: A Point Set Generation Network for 3D Object Reconstruction from a Single Image (2017) [[Paper]](http://ai.stanford.edu/~haosu/papers/SI2PC_arxiv_submit.pdf)

+:game_die: DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image (2017) [[Paper]](http://ai.stanford.edu/~haosu/papers/SI2PC_arxiv_submit.pdf) +

+ :camera: Transformation-Grounded Image Generation Network for Novel 3D View Synthesis (2017) [[Paper]](http://www.cs.unc.edu/~eunbyung/tvsn/)

+:camera: Tag Disentangled Generative Adversarial Networks for Object Image Re-rendering (2017) [[Paper]](http://static.ijcai.org/proceedings-2017/0404.pdf) +

+ +:camera: 3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks (2017) [[Paper]](http://www.cs.unc.edu/~eunbyung/tvsn/) +

+ :space_invader: Interactive 3D Modeling with a Generative Adversarial Network (2017) [[Paper]](https://arxiv.org/pdf/1706.05170.pdf)

+:camera::space_invader: Weakly supervised 3D Reconstruction with Adversarial Constraint (2017) [[Paper]](https://arxiv.org/pdf/1705.10904.pdf) +

+ +:gem: Exploring Generative 3D Shapes Using Autoencoder Networks (Autodesk 2017) [[Paper]](https://www.autodeskresearch.com/publications/exploring_generative_3d_shapes) +

+ +:pill: GRASS: Generative Recursive Autoencoders for Shape Structures (SIGGRAPH 2017) [[Paper]](http://kevinkaixu.net/projects/grass.html) +

+ ## Style Transfer Style-Content Separation by Anisotropic Part Scales (2010) [[Paper]](https://www.cs.sfu.ca/~haoz/pubs/xu_siga10_style.pdf)