diff --git a/README.md b/README.md
index 61e4ec8..d3483ae 100644
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@@ -108,7 +108,7 @@ To see a survey of RGBD datasets, check out Michael Firman's [collection](http:/
 
 <b>ScanNet (2017)</b> [[Link]](http://www.scan-net.org/)
 <br>An RGB-D video dataset containing 2.5 million views in more than 1500 scans, annotated with 3D camera poses, surface reconstructions, and instance-level semantic segmentations.
-<p align="center"><img width="50%" src="http://www.scan-net.org/img/voxel-predictions.jpg" /></p>
+<p align="center"><img width="50%" src="http://www.scan-net.org/img/annotations.png" /></p>
 
 <b>Matterport3D: Learning from RGB-D Data in Indoor Environments (2017)</b> [[Link]](https://niessner.github.io/Matterport/)
 <br>10,800 panoramic views (in both RGB and depth) from 194,400 RGB-D images of 90 building-scale scenes of private rooms. Instance-level semantic segmentations are provided for region (living room, kitchen) and object (sofa, TV) categories. 
@@ -288,6 +288,9 @@ To see a survey of RGBD datasets, check out Michael Firman's [collection](http:/
 <b>Learning Hierarchical Shape Segmentation and Labeling from Online Repositories (2017)</b> [[Paper]](http://cs.stanford.edu/~ericyi/project_page/hier_seg/index.html)
 <p align="center"><img width="50%" src="http://cs.stanford.edu/~ericyi/project_page/hier_seg/figures/teaser.jpg" /></p>
 
+:space_invader: <b>ScanNet (2017)</b> [[Paper]](https://arxiv.org/pdf/1702.04405.pdf) [[Code]](https://github.com/scannet/scannet)
+<p align="center"><img width="50%" src="http://www.scan-net.org/img/voxel-predictions.jpg" /></p>
+
 :game_die: <b>PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation (2017)</b> [[Paper]](http://stanford.edu/~rqi/pointnet/) [[Code]](https://github.com/charlesq34/pointnet)
 <p align="center"><img width="40%" src="https://web.stanford.edu/~rqi/papers/pointnet.png" /></p>
 
@@ -316,6 +319,9 @@ Parsing of Large-scale 3D Point Clouds (2017)</b> [[Paper]](https://arxiv.org/pd
 :game_die: <b>PointCNN (2018)</b> [[Paper]](https://yangyanli.github.io/PointCNN/)
 <p align="center"><img width="50%" src="http://yangyan.li/images/paper/pointcnn.png" /></p>
 
+:camera::space_invader: <b>3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation (2018)</b> [[Paper]](https://arxiv.org/pdf/1803.10409.pdf)
+<p align="center"><img width="50%" src="https://cs.stanford.edu/~adai/papers/2018/1threedmv/teaser.jpg" /></p>
+
 <a name="3d_synthesis" />
 
 ## 3D Model Synthesis/Reconstruction
@@ -438,6 +444,9 @@ _Deep Learning Methods_
 :camera: <b>Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative Networks (2017)</b> [[Paper]](http://openaccess.thecvf.com/content_cvpr_2017/papers/Soltani_Synthesizing_3D_Shapes_CVPR_2017_paper.pdf)  [[Code]](https://github.com/Amir-Arsalan/Synthesize3DviaDepthOrSil)
 <p align="center"><img width="50%" src="https://jiajunwu.com/images/spotlight_3dvae.jpg" /></p>
 
+:space_invader: <b>Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesis (2017)</b> [[Paper]](https://arxiv.org/pdf/1612.00101.pdf) [[Code]](https://github.com/angeladai/cnncomplete)
+<p align="center"><img width="50%" src="http://graphics.stanford.edu/projects/cnncomplete/teaser.jpg" /></p>
+
 :space_invader: <b>Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs (2017)</b> [[Paper]](https://arxiv.org/pdf/1703.09438.pdf) [[Code]](https://github.com/lmb-freiburg/ogn)
 <p align="center"><img width="50%" src="https://ai2-s2-public.s3.amazonaws.com/figures/2016-11-08/6c2a292bb018a8742cbb0bbc5e23dd0a454ffe3a/2-Figure2-1.png" /></p>
 
@@ -647,3 +656,6 @@ _Deep Learning Methods_
 
 <b>PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image (2018 CVPR)</b> [[Paper]](http://art-programmer.github.io/planenet/paper.pdf) [[Code]](http://art-programmer.github.io/planenet.html)
 <p align="center"><img width="50%" src="http://art-programmer.github.io/images/planenet.png" /></p>
+
+:space_invader: <b>ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans (2018)</b> [[Paper]](https://arxiv.org/pdf/1712.10215.pdf) 
+<p align="center"><img width="50%" src="https://cs.stanford.edu/~adai/papers/2018/0scancomplete/teaser.jpg" /></p>
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