From d03510b61c81e1f475105e95e50be6ef41dcad10 Mon Sep 17 00:00:00 2001 From: salehjg Date: Thu, 11 Jan 2018 16:56:18 +0330 Subject: [PATCH 1/3] Repo Links for Scene Understanding & Scene Synthesis & Style Transfer --- README.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index e3bc7f6..d275fab 100644 --- a/README.md +++ b/README.md @@ -415,10 +415,10 @@ _Deep Learning Methods_ Analogy-Driven 3D Style Transfer (2014) [[Paper]](http://www.chongyangma.com/publications/st/index.html)

-Elements of Style: Learning Perceptual Shape Style Similarity (2015) [[Paper]](http://people.cs.umass.edu/~zlun/papers/StyleSimilarity/StyleSimilarity.pdf) +Elements of Style: Learning Perceptual Shape Style Similarity (2015) [[Paper]](http://people.cs.umass.edu/~zlun/papers/StyleSimilarity/StyleSimilarity.pdf) [[Code]](https://github.com/happylun/StyleSimilarity)

-Functionality Preserving Shape Style Transfer (2016) [[Paper]](http://people.cs.umass.edu/~zlun/papers/StyleTransfer/StyleTransfer.pdf) +Functionality Preserving Shape Style Transfer (2016) [[Paper]](http://people.cs.umass.edu/~zlun/papers/StyleTransfer/StyleTransfer.pdf) [[Code]](https://github.com/happylun/StyleTransfer)

Unsupervised Texture Transfer from Images to Model Collections (2016) [[Paper]](http://ai.stanford.edu/~haosu/papers/siga16_texture_transfer_small.pdf) @@ -427,7 +427,7 @@ _Deep Learning Methods_ Learning Detail Transfer based on Geometric Features (2017) [[Paper]](http://surfacedetails.cs.princeton.edu/)

-Neural 3D Mesh Renderer (2017) [[Paper]](http://hiroharu-kato.com/projects_en/neural_renderer.html) +Neural 3D Mesh Renderer (2017) [[Paper]](http://hiroharu-kato.com/projects_en/neural_renderer.html) [[Code]](https://github.com/hiroharu-kato/neural_renderer.git)

@@ -448,7 +448,7 @@ _Deep Learning Methods_ IM2CAD [[Paper]](http://homes.cs.washington.edu/~izadinia/im2cad.html)

-Raster-to-Vector: Revisiting Floorplan Transformation (2017, ICCV) [[Paper]](http://www.cse.wustl.edu/~chenliu/floorplan-transformation.html) +Raster-to-Vector: Revisiting Floorplan Transformation (2017, ICCV) [[Paper]](http://www.cse.wustl.edu/~chenliu/floorplan-transformation.html) [[Code]](https://github.com/art-programmer/FloorplanTransformation)

@@ -475,16 +475,16 @@ _Deep Learning Methods_ DeLay: Robust Spatial Layout Estimation for Cluttered Indoor Scenes (2016) [[Paper]](http://deeplayout.stanford.edu/)

-3D Semantic Parsing of Large-Scale Indoor Spaces (2016) [[Paper]](http://buildingparser.stanford.edu/method.html) +3D Semantic Parsing of Large-Scale Indoor Spaces (2016) [[Paper]](http://buildingparser.stanford.edu/method.html) [[Code]](https://github.com/alexsax/2D-3D-Semantics)

-Single Image 3D Interpreter Network (2016) [[Paper]](http://3dinterpreter.csail.mit.edu/) +Single Image 3D Interpreter Network (2016) [[Paper]](http://3dinterpreter.csail.mit.edu/) [[Code]](https://github.com/jiajunwu/3dinn)

Deep Multi-Modal Image Correspondence Learning (2016) [[Paper]](http://www.cse.wustl.edu/~chenliu/floorplan-matching.html)

-Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks (2017) [[Paper]](http://3dvision.princeton.edu/projects/2016/PBRS/) +Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks (2017) [[Paper]](http://3dvision.princeton.edu/projects/2016/PBRS/) [[Code]](https://github.com/yindaz/pbrs) [[Code]](https://github.com/yindaz/surface_normal) [[Code]](https://github.com/fyu/dilation) [[Code]](https://github.com/s9xie/hed)

RoomNet: End-to-End Room Layout Estimation (2017) [[Paper]](https://arxiv.org/pdf/1703.06241.pdf) @@ -493,5 +493,5 @@ _Deep Learning Methods_ SUN RGB-D: A RGB-D Scene Understanding Benchmark Suite (2017) [[Paper]](http://rgbd.cs.princeton.edu/)

-Semantic Scene Completion from a Single Depth Image (2017) [[Paper]](http://sscnet.cs.princeton.edu/) +Semantic Scene Completion from a Single Depth Image (2017) [[Paper]](http://sscnet.cs.princeton.edu/) [[Code]](https://github.com/shurans/sscnet)

From 04abd3235a63d6f3787a5ddb76ed9288ab67ed17 Mon Sep 17 00:00:00 2001 From: salehjg Date: Thu, 11 Jan 2018 22:00:18 +0330 Subject: [PATCH 2/3] More Links for Deep Learning Methods Section. --- README.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index d275fab..eca0bfb 100644 --- a/README.md +++ b/README.md @@ -349,16 +349,16 @@ _Deep Learning Methods_ :camera: Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative Networks (2017) [[Paper]](http://openaccess.thecvf.com/content_cvpr_2017/papers/Soltani_Synthesizing_3D_Shapes_CVPR_2017_paper.pdf) [[Code]](https://github.com/Amir-Arsalan/Synthesize3DviaDepthOrSil)

-:space_invader: Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs (2017) [[Paper]](https://arxiv.org/pdf/1703.09438.pdf) +:space_invader: Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs (2017) [[Paper]](https://arxiv.org/pdf/1703.09438.pdf) [[Code]](https://github.com/lmb-freiburg/ogn)

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

-:space_invader: OctNetFusion: Learning Depth Fusion from Data (2017) [[Paper]](https://arxiv.org/pdf/1704.01047.pdf) +:space_invader: OctNetFusion: Learning Depth Fusion from Data (2017) [[Paper]](https://arxiv.org/pdf/1704.01047.pdf) [[Code]](https://github.com/griegler/octnetfusion)

-: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: 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) [[Code]](https://github.com/fanhqme/PointSetGeneration)

:game_die: Learning Representations and Generative Models for 3D Point Clouds (2017) [[Paper]](https://arxiv.org/pdf/1707.02392.pdf) [[Code]](https://github.com/optas/latent_3d_points) @@ -373,31 +373,31 @@ _Deep Learning Methods_ :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: Transformation-Grounded Image Generation Network for Novel 3D View Synthesis (2017) [[Paper]](http://www.cs.unc.edu/~eunbyung/tvsn/) [[Code]](https://github.com/silverbottlep/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/) +:camera: 3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks (2017) [[Paper]](http://www.cs.unc.edu/~eunbyung/tvsn/) [[Code]](https://github.com/happylun/SketchModeling)

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

: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) +:pill: GRASS: Generative Recursive Autoencoders for Shape Structures (SIGGRAPH 2017) [[Paper]](http://kevinkaixu.net/projects/grass.html) [[Code]](https://github.com/junli-lj/grass) [[code]](https://github.com/kevin-kaixu/grass_pytorch)

:gem: Mesh-based Autoencoders for Localized Deformation Component Analysis (2017) [[Paper]](https://arxiv.org/pdf/1709.04304.pdf)

-:gem: Neural 3D Mesh Renderer (2017) [[Paper]](http://hiroharu-kato.com/projects_en/neural_renderer.html) +:gem: Neural 3D Mesh Renderer (2017) [[Paper]](http://hiroharu-kato.com/projects_en/neural_renderer.html) [[Code]](https://github.com/hiroharu-kato/neural_renderer.git)

:game_die::space_invader: Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55 (2017) [[Paper]](https://arxiv.org/pdf/1710.06104.pdf) From 8748b6b7be59dcc6ddf16701ada1980108acd003 Mon Sep 17 00:00:00 2001 From: salehjg Date: Thu, 11 Jan 2018 22:26:00 +0330 Subject: [PATCH 3/3] more links and fixes. --- README.md | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index eca0bfb..7cc8051 100644 --- a/README.md +++ b/README.md @@ -140,31 +140,31 @@ To see a survey of RGBD datasets, check out Michael Firman's [collection](http:/ :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)

-: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: 3D GAN: Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling (2016) [[Paper]](https://arxiv.org/pdf/1610.07584.pdf) [[Code]](https://github.com/zck119/3dgan-release)

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

-:space_invader: OctNet: Learning Deep 3D Representations at High Resolutions (2017) [[Paper]](https://github.com/griegler/octnet) +:space_invader: OctNet: Learning Deep 3D Representations at High Resolutions (2017) [[Paper]](https://arxiv.org/pdf/1611.05009.pdf) [[Code]](https://github.com/griegler/octnet)

-:space_invader: O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis (2017) [[Paper]](http://wang-ps.github.io/O-CNN) +:space_invader: O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis (2017) [[Paper]](http://wang-ps.github.io/O-CNN) [[Code]](https://github.com/Microsoft/O-CNN)

-:space_invader: Orientation-boosted voxel nets for 3D object recognition (2017) [[Paper]](https://lmb.informatik.uni-freiburg.de/Publications/2017/SZB17a/) +:space_invader: Orientation-boosted voxel nets for 3D object recognition (2017) [[Paper]](https://lmb.informatik.uni-freiburg.de/Publications/2017/SZB17a/) [[Code]](https://github.com/lmb-freiburg/orion)

-:game_die: PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation (2017) [[Paper]](http://stanford.edu/~rqi/pointnet/) +:game_die: PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation (2017) [[Paper]](http://stanford.edu/~rqi/pointnet/) [[Code]](https://github.com/charlesq34/pointnet)

-:game_die: PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space (2017) [[Paper]](https://arxiv.org/pdf/1706.02413.pdf) +:game_die: PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space (2017) [[Paper]](https://arxiv.org/pdf/1706.02413.pdf) [[Code]](https://github.com/charlesq34/pointnet2)

-:camera: Feedback Networks (2017) [[Paper]](http://feedbacknet.stanford.edu/) +:camera: Feedback Networks (2017) [[Paper]](http://feedbacknet.stanford.edu/) [[Code]](https://github.com/amir32002/feedback-networks)

:game_die: Escape from Cells: Deep Kd-Networks for The Recognition of 3D Point Cloud Models (2017) [[Paper]](http://www.arxiv.org/pdf/1704.01222.pdf) @@ -179,7 +179,7 @@ To see a survey of RGBD datasets, check out Michael Firman's [collection](http:/ Object Detection in 3D Scenes Using CNNs in Multi-view Images (2016) [[Paper]](https://stanford.edu/class/ee367/Winter2016/Qi_Report.pdf)

-Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images (2016) [[Paper]](http://dss.cs.princeton.edu/) +Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images (2016) [[Paper]](http://dss.cs.princeton.edu/) [[Code]](https://github.com/shurans/DeepSlidingShape)

DeepContext: Context-Encoding Neural Pathways for 3D Holistic Scene Understanding (2016) [[Paper]](http://deepcontext.cs.princeton.edu/) @@ -203,19 +203,19 @@ To see a survey of RGBD datasets, check out Michael Firman's [collection](http:/ Unsupervised Co-Segmentation of a Set of Shapes via Descriptor-Space Spectral Clustering (2011) [[Paper]](https://www.cs.sfu.ca/~haoz/pubs/sidi_siga11_coseg.pdf)

-Single-View Reconstruction via Joint Analysis of Image and Shape Collections (2015) [[Paper]](https://www.cs.utexas.edu/~huangqx/modeling_sig15.pdf) +Single-View Reconstruction via Joint Analysis of Image and Shape Collections (2015) [[Paper]](https://www.cs.utexas.edu/~huangqx/modeling_sig15.pdf) [[Code]](https://github.com/huangqx/image_shape_align)

-3D Shape Segmentation with Projective Convolutional Networks (2017) [[Paper]](http://people.cs.umass.edu/~kalo/papers/shapepfcn/) +3D Shape Segmentation with Projective Convolutional Networks (2017) [[Paper]](http://people.cs.umass.edu/~kalo/papers/shapepfcn/) [[Code]](https://github.com/kalov/ShapePFCN)

Learning Hierarchical Shape Segmentation and Labeling from Online Repositories (2017) [[Paper]](http://cs.stanford.edu/~ericyi/project_page/hier_seg/index.html)

-:game_die: PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation (2017) [[Paper]](http://stanford.edu/~rqi/pointnet/) +:game_die: PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation (2017) [[Paper]](http://stanford.edu/~rqi/pointnet/) [[Code]](https://github.com/charlesq34/pointnet)

-:game_die: PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space (2017) [[Paper]](https://arxiv.org/pdf/1706.02413.pdf) +:game_die: PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space (2017) [[Paper]](https://arxiv.org/pdf/1706.02413.pdf) [[Code]](https://github.com/charlesq34/pointnet2)

:game_die: 3D Graph Neural Networks for RGBD Semantic Segmentation (2017) [[Paper]](http://www.cs.toronto.edu/~rjliao/papers/iccv_2017_3DGNN.pdf) @@ -242,7 +242,7 @@ Parsing of Large-scale 3D Point Clouds (2017) [[Paper]](https://arxiv.org/pd _Parametric Morphable Model-based methods_ -A Morphable Model For The Synthesis Of 3D Faces (1999) [[Paper]](http://gravis.dmi.unibas.ch/publications/Sigg99/morphmod2.pdf)[[Github]](https://github.com/MichaelMure/3DMM) +A Morphable Model For The Synthesis Of 3D Faces (1999) [[Paper]](http://gravis.dmi.unibas.ch/publications/Sigg99/morphmod2.pdf)[[Code]](https://github.com/MichaelMure/3DMM)

The Space of Human Body Shapes: Reconstruction and Parameterization from Range Scans (2003) [[Paper]](http://grail.cs.washington.edu/projects/digital-human/pub/allen03space-submit.pdf) @@ -319,10 +319,10 @@ _Deep Learning Methods_ :camera: View Synthesis by Appearance Flow (2016) [[Paper]](https://people.eecs.berkeley.edu/~tinghuiz/papers/eccv16_appflow.pdf) [[Code]](https://github.com/tinghuiz/appearance-flow)

-:space_invader: Voxlets: Structured Prediction of Unobserved Voxels From a Single Depth Image (2016) [[Paper]](http://visual.cs.ucl.ac.uk/pubs/depthPrediction/http://visual.cs.ucl.ac.uk/pubs/depthPrediction/) +:space_invader: Voxlets: Structured Prediction of Unobserved Voxels From a Single Depth Image (2016) [[Paper]](http://visual.cs.ucl.ac.uk/pubs/depthPrediction/http://visual.cs.ucl.ac.uk/pubs/depthPrediction/) [[Code]](https://github.com/mdfirman/voxlets)

-:space_invader: 3D-R2N2: 3D Recurrent Reconstruction Neural Network (2016) [[Paper]](http://cvgl.stanford.edu/3d-r2n2/) +:space_invader: 3D-R2N2: 3D Recurrent Reconstruction Neural Network (2016) [[Paper]](http://cvgl.stanford.edu/3d-r2n2/) [[Code]](https://github.com/chrischoy/3D-R2N2)

:space_invader: Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision (2016) [[Paper]](https://eng.ucmerced.edu/people/jyang44/papers/nips16_ptn.pdf)