Update README.md

README.md

@@ -650,7 +650,7 @@ _Deep Learning Methods_
 <p align="center"><img width="50%" src="http://text2shape.stanford.edu/figures/pull.png" /></p>
 
 :space_invader::gem::camera: <b>Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation (2018)</b>  [[Paper]](https://arxiv.org/abs/1802.09987) [[Code]](https://github.com/EdwardSmith1884/Multi-View-Silhouette-and-Depth-Decomposition-for-High-Resolution-3D-Object-Representation)
-<p align="center"><img width="60%" src="imgs/decomposition_new.png" /> <img width="60%" src="imgs/256.png" /></p>
+<p align="center"><img width="60%" src="imgs/decomposition_new.png" /> <img width="60%" src="https://github.com/timzhang642/3D-Machine-Learning/blob/master/imgs/Multi-View%20Silhouette%20and%20Depth%20Decomposition%20for%20High%20Resolution%203D%20Object%20Representation.png" /></p>
 
 :space_invader::gem::camera: <b>Pixels, voxels, and views: A study of shape representations for single view 3D object shape prediction (2018 CVPR)</b>  [[Paper]](https://arxiv.org/abs/1804.06032)
 <p align="center"><img width="60%" src="imgs/pixels-voxels-views-rgb2mesh.png" /> </p>
@@ -694,6 +694,9 @@ _Deep Learning Methods_
 :space_invader: <b>Learning to Infer and Execute 3D Shape Programs (2019))</b> [[Paper]](https://arxiv.org/pdf/1901.05103.pdf)
 <p align="center"><img width="50%" src="https://pbs.twimg.com/media/DxFaW-mU8AEo9wc.jpg" /></p>
 
+:gem: <b>Learning View Priors for Single-view 3D Reconstruction (CVPR 2019)</b> [[Paper]](http://hiroharu-kato.com/projects_en/view_prior_learning.html)
+<p align="center"><img width="50%" src="" /></p>
+
 <a name="material_synthesis" />
 
 ## Texture/Material Analysis and Synthesis
@@ -836,6 +839,9 @@ using Style-Synchonized GANs (2018 SIGGRAPH Asia)</b> [[Paper]](http://geometry.
 <b>SceneSuggest: Context-driven 3D Scene Design (2017)</b> [[Paper]](https://arxiv.org/pdf/1703.00061.pdf)
 <p align="center"><img width="50%" src="https://github.com/timzhang642/3D-Machine-Learning/blob/master/imgs/SceneSuggest%20-Context-driven%203D%20Scene%20Design%20(2017).png" /></p>
 
+<b>A fully end-to-end deep learning approach for real-time simultaneous 3D reconstruction and material recognition (2017)</b> [[Paper]](https://arxiv.org/pdf/1703.04699v1.pdf)
+<p align="center"><img width="50%" src="https://github.com/timzhang642/3D-Machine-Learning/blob/master/imgs/A%20fully%20end-to-end%20deep%20learning%20approach%20for%20real-time%20simultaneous%203D%20reconstruction%20and%20material%20recognition%20(2017).png" /></p>
+
 <b>Human-centric Indoor Scene Synthesis Using Stochastic Grammar (2018, CVPR)</b>[[Paper]](http://web.cs.ucla.edu/~syqi/publications/cvpr2018synthesis/cvpr2018synthesis.pdf) [[Supplementary]](http://web.cs.ucla.edu/~syqi/publications/cvpr2018synthesis/cvpr2018synthesis_supplementary.pdf) [[Code]](https://github.com/SiyuanQi/human-centric-scene-synthesis)
 <p align="center"><img width="50%" src="http://web.cs.ucla.edu/~syqi/publications/thumbnails/cvpr2018synthesis.gif" /></p>
 
@@ -936,4 +942,6 @@ with Per-Pixel Ground Truth using Stochastic Grammars (2018)</b> [[Paper]](https
 
 <b>Automatic 3D Indoor Scene Modeling from Single Panorama (2018 CVPR)</b> [[Paper]](http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang_Automatic_3D_Indoor_CVPR_2018_paper.pdf) <p align="center"><img width="50%" src="https://github.com/timzhang642/3D-Machine-Learning/blob/master/imgs/Automatic%203D%20Indoor%20Scene%20Modeling%20from%20Single%20Panorama%20(2018%20CVPR).jpeg" /></p>
 
-<b>Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding (2019 CVPR)</b> [[Paper]](https://arxiv.org/pdf/1902.09777.pdf) [[Code]](https://github.com/svip-lab/PlanarReconstruction) <p align="center"><img width="50%" src="https://github.com/svip-lab/PlanarReconstruction/blob/master/misc/pipeline.jpg" /></p>
+<b>Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding (2019 CVPR)</b> [[Paper]](https://arxiv.org/pdf/1902.09777.pdf) [[Code]](https://github.com/svip-lab/PlanarReconstruction) <p align="center"><img width="50%" src="https://github.com/svip-lab/PlanarReconstruction/blob/master/misc/pipeline.jpg" /></p>
+
+<b>3D-Aware Scene Manipulation via Inverse Graphics (NeurIPS 2018)</b> [[Paper]](http://3dsdn.csail.mit.edu/) [[Code]](https://github.com/svip-lab/PlanarReconstruction) <p align="center"><img width="50%" src="http://3dsdn.csail.mit.edu/images/teaser.png" /></p>