Reading_List

Reading list on deep learning.

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3D GAN && PointCloud

• PointNet: Charles R. Qi, et al. "PointNet: Deep Learning on Point Sets for 3D Classification * and Segmentation" In 2017 CVPR

• PointNet++: Charles R. Qi, et al. "PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space" In 2017 NIPS

• FrustumNet: Charles R. Qi, et al. "Frustum PointNets for 3D Object Detection from RGB-D Data" In 2018 CVPR

• 3D-GAN: Jiajun Wu, et al."Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling" In 2016 NIPS

• IW-GAN:Edward J. Smith, et al. "Improved Adversarial Systems for 3D Object Generation and Reconstruction" arXiv:1707.09557.

• RecGAN: Bo Yang, et al. "3D Object Reconstruction from a Single Depth View with Adversarial Learning" In 2017 ICCV workshop

• GAL: Jiang Li, et al. "GAL: Geometric Adversarial Loss for Single-View 3D-Object Reconstruction" In 2018 ECCV

• PSGN: Haoqiang Fan, et al."A Point Set Generation Network for 3D Object Reconstruction from a Single Image" In 2017 CVPR

• PCN: Wentao Yuan, et al. "PCN: Point Completion Network." In 2018 3DV

• Dense Rec: Chen-Hsuan Lin, et al."Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction" In 2018 AAAI

• Point Cloud GAN: Chun-Liang Li, et al. "Point Cloud GAN" arXiv:1810.05795.

• PCPNet: Paul Guerrero, et al. "PCPNET: Learning Local Shape Properties from Raw Point Clouds" In 2018 EG

• LRGM: Panos Achlioptas, et al."Learning Representations and Generative Models for 3D Point Clouds" In 2018 ICLR workshop

• P2PNet: KANGXUE YIN, et al."P2P-NET: Bidirectional Point Displacement Net for Shape Transform" In 2018 Siggraph

• POINTCLEANNET: Marie-Julie Rakotosaona, et al. "POINTCLEANNET: Learning to Denoise and Remove Outliers from Dense Point Clouds" arXiv: 1901.01060

• PPFNet: Haowen Deng, et al. "PPFNet: Global Context Aware Local Features for Robust 3D Point Matching" In 2018 CVPR

• PPF-FoldNet: Haowen Deng, et al. "PPF-FoldNet: Unsupervised Learnning of Rotation Invariant 3D Local Descriptors" In 2018 ECCV

• PPPU: Wang Yifan, et al. "Patch-based Progressive 3D Point Set Upsampling " In 2019 CVPR

• L2S: Oren Dovrat, et al. "Learning to Sample" In 2019 CVPR

• PCC: Xuelin Chen, et al. "Unpaired Point Cloud Completion on Real Scans using Adversarial Training" arXiv:1904.00069

• PointConv: Wenxuan Wu, et al. "PointConv: Deep Convolutional Networks on 3D Point Clouds". In 2019 CVPR

• PointCNN: Yangyan Li, et al. "PointCNN: Convolution On X-Transformed Points". In 2018 NIPS

• PointWeb: Hengshuang Zhao, et al. "PointWeb: Enhancing Local Neighborhood Features for Point Cloud Processing" In 2019 CVPR

• Point-Capsule: Yongheng Zhao, et al. "3D Point-Capsule Networks" arXiv:1812.10775

• CPL: Ehsan Nezhadarya, et al. "Adaptive Hierarchical Down-Sampling for Point Cloud Classification" arXiv:1904.08506

• PCAN: Wenxiao Zhang, et al. "PCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval" In 2019 CVPR

• PN_VLAD: Mikaela Angelina Uy, et al. "PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition" In 2018 CVPR

• RS-CNN: Yongcheng Liu, et al. "Relation-Shape Convolutional Neural Network for Point Cloud Analysis" In 2019 CVPR

• GPC: Chong Xiang, et al. "Generating 3D Adversarial Point Clouds" In 2019 CVPR

• SO-NET: Jiaxin Li, et al. "SO-Net: Self-Organizing Network for Point Cloud Analysis" In 2018 CVPR

• PU-Net: Lequan Yu, et al. "PU-Net: Point Cloud Upsampling Network" In 2018 CVPR

• EC-Net: Lequan Yu, et al. "EC-Net: an Edge-aware Point set Consolidation Network" In 2018 ECCV

• LSGC: Chu Wang, et al. "Local Spectral Graph Convolution for Point Set Feature Learning" In 2018 ECCV

• Gconv: Diego Valsesia, et al. " Learning Localized Generative Models for 3D Point Clouds via Graph Convolution" In 2019 ICLR

• Scan2Mesh: Angela Dai, et al. "Scan2Mesh: From Unstructured Range Scans to 3D Meshes." In 2019 CVPR

• ContrastNet: Ling Zhang, et al. "Unsupervised Feature Learning for Point Cloud by Contrasting and Clustering With Graph Convolutional Neural Network" arXiv:1904.12359

• VoteNet: Charles R. Qi, et al. "Deep Hough Voting for 3D Object Detection in Point Clouds" arXiv:1904.09664

• StructureNet: Zhidong Liang, et al. "3D Graph Embedding Learning with a Structure-aware Loss Function for Point Cloud Semantic Instance Segmentation" arXiv:1902.05247

• DeepGCN: Guohao Li, et al. "Can GCNs Go as Deep as CNNs?" arXiv:1904.03751

• RGCNN: Gusi Te, et al. "RGCNN: Regularized Graph CNN for Point Cloud Segmentation" In 2018 ACM MM

• SRN: Yueqi Duan, et al. "Structural Relational Reasoning of Point Clouds" In 2019 CVPR

• Tree-GAN: Dong Wook Shu, et al. "3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions" arXiv:1905.06292

• KPConv: Hugues Thomas, et al. “KPConv: Flexible and Deformable Convolution for Point Clouds” arXiv:1904.08889

• PointWise:Matan Shoef, et al. "PointWise: An Unsupervised Point-wise Feature Learning Network" arXiv:1901.04544

• GAPNet: Can Chen, et al. "GAPNet: Graph Attention based Point Neural Network for Exploiting Local Feature of Point Cloud" arXiv:1905.08705

• GACNet: , et al. "Graph Attention Convolution for Point Cloud Segmentation" In CVPR 2019

• DensePCR: Priyanka Mandikal, et al. "Dense 3D Point Cloud Reconstruction Using a Deep Pyramid Network" arXiv:1901.08906

• G-NPC: Xianzhi Li, et al. "Non-Local Low-Rank Normal Filtering for Mesh Denoising" In 2018 PG

• AGCN: Zhuyang Xie, et al. "Point Clouds Learning with Attention-based Graph Convolution Networks" arXiv: 1905.13445

• MeshNet: Yutong Feng, et al. "MeshNet: Mesh Neural Network for 3D Shape Representation" arXiv: 1811.11424

• TopNet: Lyne P. Tchapmi et al."TopNet: Structural Point Cloud Decoder." In CVPR 2019

• Nesti-Net: Yizhak Ben-Shabat et al."Nesti-Net: Normal Estimation for Unstructured 3D Point Clouds using Convolutional Neural Networks." In CVPR 2019

• LOGAN: Kangxue Yin et al."LOGAN: Unpaired Shape Transform in Latent Overcomplete Space." In Siggraph Asia 2019

• PointFlow: Guandao Yang et al. "PointFlow : 3D Point Cloud Generation with Continuous Normalizing Flow" In ICCV 2019

Image GAN

• GAN: Goodfellow, Ian, et al. "Generative adversarial nets." In 2014 NIPS .

• cGAN: Mirza, Mehdi, and Simon Osindero. "Conditional generative adversarial nets." arXiv preprint arXiv:1411.1784 (2014).

• S²-GAN: Xiaolong Wang, et al. "Generative Image Modeling using Style and Structure Adversarial Networks." In 2016 ECCV

• DCGAN: Radford, et al.. "Unsupervised representation learning with deep convolutional generative adversarial networks." In 2016 ICLR

• Pixel2Pixel: Isola, Phillip, et al. "Image-to-image translation with conditional adversarial networks." In 2017 CVPR

• SRGAN: Christian,Ledig, et al. "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network." In 2017 CVPR.

• AdaIN: Xun Huang , et al. "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization ." In 2017 ICCV

• CycleGAN：Zhu, Jun-Yan, et al. "Unpaired image-to-image translation using cycle-consistent adversarial networks." In 2017 ICCV.

• BicycleGAN：Zhu, Jun-Yan, et al. "Toward Multimodal Image-to-Image Translation." In 2017 NIPS.

• Least square loss :Xudong, Mao , et al. "Least Squares Generative Adversarial Networks ." In 2017 ICCV.

• StackGAN: Han Zhang, et al. "StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks ." In 2017 ICCV.

• StackGAN++: Han Zhang, et al. "StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks ." In 2018 TPAMI.

• TTUR: Martin Heusel, et al. "GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium ." In 2017 NIPS.

• SGAN: Xun Huang , et al. "Stacked Generative Adversarial Networks ." In 2017 CVPR.

• Style-Based GAN: Tero Karras , et al. "A Style-Based Generator Architecture for Generative Adversarial Networks ." NVIDIA. In 2018 arXiv.

• StarGAN: Choi, Yunjey, et al. "Stargan: Unified generative adversarial networks for multi-domain image-to-image translation." In CVPR 2018.

• DISSECTIONGAN: Zhu, Jun-Yan, et al. "GAN DISSECTION: VISUALIZING AND UNDERSTANDING GENERATIVE ADVERSARIAL NETWORKS ." arXiv:1811.10597.

• GDWTC: Wonwoong Cho, et al. "Image-to-Image Translation via Group-wise Deep Whitening and Coloring Transformation" arXiv:1812.09912.

• Latent Filter GAN: Yazeed Alharbi, et al."Latent Filter Scaling for Multimodal Unsupervised Image-to-Image Translation." In CVPR 2019.

• CariGAN: KAIDI CAO, et al. "CariGANs: Unpaired Photo-to-Caricature Translation." In 2018 Siggraph.

• AttnGAN: Tao Xu, et al. "AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks." In 2018 CVPR

• Pixel2PixelHD: Ting-Chun Wang, et al. "High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs." In 2018 CVPR

• Attention-GAN: Xinyuan Chen, et al. "Attention-GAN for Object Transfiguration in Wild Images." In 2018 ECCV

• DRIT: Hsin-Ying Lee, et al. "Diverse Image-to-Image Translation via Disentangled Representations." In 2018 ECCV

• Contextual GAN: Yongyi Lu, et al. "Image Generation from Sketch Constraint Using Contextual GAN." In 2018 ECCV

• MUINT: Xun Huang, et al. "Multimodal Unsupervised Image-to-Image Translation" In 2018 ECCV

• Recycle-GAN: Aayush Bansal , et al. "Recycle-GAN: Unsupervised Video Retargeting" In 2018 ECCV

• Sub-GAN: Jie Liang, et al."Sub-GAN: An Unsupervised Generative Model via Subspaces" In 2018 ECCV

• Stack CycleGAN:Minjun Li, et al. "Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks " In 2018 ECCV

• Progressive GAN: Tero Karras , et al."PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION" In 2018 ICLR

• SAGAN: Han Zhang, et al. "Self-Attention Generative Adversarial Networks" In 2018 ICLR

• SN: Takeru Miyato, et al. "SPECTRAL NORMALIZATION FOR GENERATIVE ADVERSARIAL NETWORKS " In 2018 ICLR

• Augmented CycleGAN: Amjad Almahairi , et al. "Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data" In 2018 ICML

• BigGAN: Andrew Brock, et al."LARGE SCALE GAN TRAINING FOR HIGH FIDELITY NATURAL IMAGE SYNTHESIS " In ICLR 2019

• InstaGAN: Sangwoo Mo, et al. "INSTANCE-AWARE IMAGE-TO-IMAGE TRANSLATION " In 2019 ICLR

• RGAN: Alexia Jolicoeur-Martineau, et al. "The relativistic discriminator: a key element missing from standard GAN" In 2019 ICLR

• Pixel-Shuffer: Wenzhe Shi, et al. "Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network" In CVPR 2016

• Degradation GAN: Adrian Bulat et al."To learn image super-resolution, use a GAN to learn how to do image degradation first." In ECCV 2018

• DANet: Jun Fu et al. "Dual Attention Network for Scene Segmentation." In CVPR 2019

• FineGAN: Krishna Kumar Singh et al. "FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery." In CVPR 2019

• TransGaGa: Wayne Wu et al. "TransGaGa: Geometry-Aware Unsupervised Image-to-Image Translation." In CVPR 2019

• Deblur-GAN: Boyu Lu et al. "Unsupervised Domain-Specific Deblurring via Disentangled Representations." In CVPR 2019

GNN

• Peter W. Battaglia, et al. "Relational inductive biases, deep learning, and graph networks" arXiv: 1806.01261

NLP

• Multi Agent :"MULTI-AGENT DUAL LEARNING" In ICLR 2019