└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # Reading_List 2 | Reading list on deep learning. 3 | 4 | *** 5 | ## Tutorial 6 | * **SSL**: Thang Luong. "Learning from Unlabeled Data". 7 | 8 | 9 | ## Survey 10 | 11 | * **Geometric Primitives**: Shaobo Xia et al."Geometric Primitives in LiDAR Point Clouds: A Review" 12 | 13 | * **Surface Reconstrcution**: Matthew Berger et al."A Survey of Surface Reconstruction from Point Clouds". CGF 2016 14 | 15 | * **3D Survey**: Ying Li et al. "Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review" arXiv:2005.09830 (Waterloo) 16 | 17 | * **3D Survey**: Yulan Guo, et al. "Deep Learning for 3D Point Clouds: A Survey" arXiv:1912.12033 (NUDT) 18 | 19 | * **I2I Survey**: Yingxue Pang et al. "Image-to-Image Translation: Methods and Applications" arXiv 2101.08629 (USTC) 20 | 21 | * **GAN Survey**: Zhengwei Wang et al. "Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy" ACM Computing Surveys 2020 (Trinity College Dublin) 22 | 23 | * **GAN Survey**: Abdul Jabbar et al. "A Survey on Generative Adversarial Networks:Variants, Applications, and Training". 2020 (ZJU) 24 | 25 | * **ViT Survey**: Kai Han et al. "A Survey on Visual Transformer" arXiv 2012.12556 (Noah) 26 | 27 | * **ViT Survey**: Salman Khan et al. "Transformers in Vision: A Survey" arXiv 2101.01169 (MBZ) 28 | 29 | ## Metric learning 30 | 31 | * **PointMixup**: Yunlu Chen et al. "PointMixup: Augmentation for Point Clouds" In ECCV 2020 (University of Amsterdam) 32 | 33 | * **Embedding Expansion**: Byungsoo Ko et al. "Embedding Expansion: Augmentation in Embedding Space for Deep Metric Learning" In CVPR 2020 (NAVER) 34 | 35 | * **BALMS**: Jiawei Ren et al."Balanced Meta-Softmax for Long-Tailed Visual Recognition" In NIPS 2020 (NTU) 36 | 37 | 38 | ## Biomolecule Modelling 39 | 40 | * **dMaSIF**: Freyr Sverrisson et al."Fast End-to-End Learning on Protein Surfaces". CVPR 2021 (EPFL) 41 | 42 | 43 | ## 3D Mesh && PointCloud 44 | 45 | * **VSL**: Shikun Liu et al."Learning a Hierarchical Latent-Variable Model of 3D Shapes" 3DV 2018 (ICL) 46 | 47 | * **IMLSNet**: Shi-Lin Liu et al."Deep Implicit Moving Least-Squares Functions for 3D Reconstruction" CVPR 2021 (MSRA) 48 | 49 | * **GeoNet**: Tong He et al."GeoNet: Deep Geodesic Networks for Point Cloud Analysis" CVPR 2019 (UCLA) 50 | 51 | * **Spare-Net**: Chulin Xie et al. "Style-based Point Generator with Adversarial Rendering for Point Cloud Completion". CVPR 2021 (UIUC) 52 | 53 | * **GPDNet**: Pistilli, Francesca et al. "Learning Graph-Convolutional Representationsfor Point Cloud Denoising". ECCV 2020 (Politecnico di Torino, Italy) 54 | 55 | * **DMRDenoise**: Luo, Shitong et al. "Differentiable Manifold Reconstruction for Point Cloud Denoising". ACMMM 2021 (PKU) 56 | 57 | * **Rethinking Sampling**: He Wang et al. "Rethinking Sampling in 3D Point Cloud Generative Adversarial Networks" arXiv:2006.07029 (Standford) 58 | 59 | * **UDS**: Yi Shi et al. "Unsupervised Deep Shape Descriptor with Point Distribution Learning" In CVPR 2020 (NYU) 60 | 61 | * **MS-cGAN**: Rundi Wu et al. "Multimodal Shape Completion via Conditional Generative Adversarial Networks" In ECCV 2020 (PKU) 62 | 63 | * **LG-GAN**: Hang Zhou et al. "LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud Based Deep Networks" In CVPR 2020 (USTC) 64 | 65 | * **DUP-Net**: Hang Zhou et al. "DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense" In ICCV 2019 (USTC) 66 | 67 | * **GvG-P**: Xiaoyi Dong et al. "Self-Robust 3D Point Recognition via Gather-Vector Guidance" In CVPR 2020 (USTC) 68 | 69 | * **PosPool**: Ze Liu et al."A Closer Look at Local Aggregation Operators in Point Cloud Analysis" ECCV 2020 (NSTC) 70 | 71 | * **PointNL**: Mingmei Cheng et al. " Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation " IROS 2020 (NUST) 72 | 73 | * **PointContrast**: Saining Xie et al. "PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding" ECCV 2020 (FAIR) 74 | 75 | * **SVCN**: Li Yi et al. "Complete & Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds". arXiv 2007 (Google) 76 | 77 | * **PDGN**: Le Hui et al. "Progressive Point Cloud Deconvolution Generation Network". ECCV 2020 (NJUST) 78 | 79 | * **ACNe**: Weiwei Sun et al. "ACNe: Attentive Context Normalization for Robust Permutation-Equivariant Learning". CVPR 2020 (University of Victoria) 80 | 81 | * **Spatial Transformer**: Jiayun Wang et al. "Spatial Transformer for 3D Point Clouds" arXiv:1906.10887 (UC Berkeley) 82 | 83 | * **MOPS-Net**: Yue Qian et al. "MOPS-Net: A Matrix Optimization-driven Network for Task-Oriented 3D Point Cloud Downsampling" arXiv:2005.00383 (CityU) 84 | 85 | * **C-Flow**: Albert Pumarola et al. "C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds". In CVPR 2020 (Google) 86 | 87 | * **PointGMM**: Amir Hertz et al. "PointGMM: a Neural GMM Network for Point Clouds". In CVPR 2020 (TAU) 88 | 89 | * **GLR**: Yongming Rao et al. "Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds". In CVPR 2020 (THU) 90 | 91 | * **Grid-GCN**: Qiangeng Xu et al. "Grid-GCN for Fast and Scalable Point Cloud Learning". In CVPR 2020 (USC) 92 | 93 | * **TreeGAN**: Dong Wook Shu et al. "3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions". In ICCV 2019 (CAU) 94 | 95 | * **SA-Net**: Xin Wen et al. "Point Cloud Completion by Skip-attention Network with Hierarchical Folding". arXiv:2005.03871 (THU) 96 | 97 | * **Cascaded**: Xiaogang Wang et al. "Cascaded Refinement Network for Point Cloud Completion". In CVPR 2020 (NUS) 98 | 99 | * **PF-Net**: Zitian Huang, et al. "PF-Net: Point Fractal Network for 3D Point Cloud Completion" In CVPR 2020 (SJTU) 100 | 101 | * **FPConv**: Yiqun Lin et al. "FPConv: Learning Local Flattening for Point Convolution". In CVPR 2020 (CHKU SZ) 102 | 103 | * **3DStructurePoints**: Nenglun Chen et al. "Unsupervised Learning of Intrinsic Structural Representation Points". In CVPR 2020 (HKU) 104 | 105 | * **DPDist**: Dahlia Urbach et al. "DPDist:Comparing Point Clouds Using Deep Point Cloud Distance" arXiv:2004.11784 106 | 107 | * **Mesh R-CNN**: Georgia Gkioxari et al. "Mesh R-CNN." In ICCV 2019 108 | 109 | * **TMNet**: Junyi Pan et al. "Deep Mesh Reconstruction from Single RGB Images via Topology Modification Networks." In ICCV 2019 110 | 111 | * **Pixel2Mesh++**: Chao Wen et al. "Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation." In ICCV 2019 112 | 113 | * **Pixel2Mesh**: Nanyang Wang et al. "Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images." In ECCV 2018 114 | 115 | * **Scan2Mesh**: Angela Dai, et al. "Scan2Mesh: From Unstructured Range Scans to 3D Meshes" In ICCV 2019 116 | 117 | * **PointGroup**: Jiang Li, et al. "PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation" In CVPR2020 118 | 119 | * **DetDA**: Martin Hahner, et al. "Quantifying Data Augmentation for LiDAR based 3D Object Detection" arXiv:2004.01643 120 | 121 | * **DCM-Net**: Jonas Schult, et al. "DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes" In CVPR2020 122 | 123 | * **PCRNet**: Vinit Sarode, et al. "PCRNet: Point Cloud Registration Network using PointNet Encoding" arXiv:1908.07906. 124 | 125 | * **PointNetLK**: Yasuhiro Aoki, et al. "PointNetLK: Robust & Efficient Point Cloud Registration using PointNet" In 2019 CVPR 126 | 127 | * **DPAM**: Jinxian Liu, et al. "Dynamic Points Agglomeration for Hierarchical Point Sets Learning" In 2019 ICCV 128 | 129 | * **PointNet**: Charles R. Qi, et al. "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" In 2017 CVPR 130 | 131 | * **PointNet++**: Charles R. Qi, et al. "PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space" In 2017 NIPS 132 | 133 | * **FrustumNet**: Charles R. Qi, et al. "Frustum PointNets for 3D Object Detection from RGB-D Data" In 2018 CVPR 134 | 135 | * **3D-GAN**: Jiajun Wu, et al."Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling" In 2016 NIPS 136 | 137 | * **IW-GAN**:Edward J. Smith, et al. "Improved Adversarial Systems for 3D Object Generation and Reconstruction" arXiv:1707.09557. 138 | 139 | * **RecGAN**: Bo Yang, et al. "3D Object Reconstruction from a Single Depth View with Adversarial Learning" In 2017 ICCV workshop 140 | 141 | * **GAL**: Jiang Li, et al. "GAL: Geometric Adversarial Loss for Single-View 3D-Object Reconstruction" In 2018 ECCV 142 | 143 | * **PSGN**: Haoqiang Fan, et al."A Point Set Generation Network for 3D Object Reconstruction from a Single Image" In 2017 CVPR 144 | 145 | * **PCN**: Wentao Yuan, et al. "PCN: Point Completion Network." In 2018 3DV 146 | 147 | * **Dense Rec**: Chen-Hsuan Lin, et al."Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction" In 2018 AAAI 148 | 149 | * **Point Cloud GAN**: Chun-Liang Li, et al. "Point Cloud GAN" arXiv:1810.05795. 150 | 151 | * **PCPNet**: Paul Guerrero, et al. "PCPNET: Learning Local Shape Properties from Raw Point Clouds" In 2018 EG 152 | 153 | * **LRGM**: Panos Achlioptas, et al."Learning Representations and Generative Models for 3D Point Clouds" In 2018 ICLR workshop 154 | 155 | * **P2PNet**: KANGXUE YIN, et al."P2P-NET: Bidirectional Point Displacement Net for Shape Transform" In 2018 Siggraph 156 | 157 | * **POINTCLEANNET**: Marie-Julie Rakotosaona, et al. "POINTCLEANNET: Learning to Denoise and Remove Outliers from Dense Point Clouds" arXiv: 1901.01060 158 | 159 | * **PPFNet**: Haowen Deng, et al. "PPFNet: Global Context Aware Local Features for Robust 3D Point Matching" In 2018 CVPR 160 | 161 | * **PPF-FoldNet**: Haowen Deng, et al. "PPF-FoldNet: Unsupervised Learnning of Rotation Invariant 3D Local Descriptors" In 2018 ECCV 162 | 163 | * **PPPU**: Wang Yifan, et al. "Patch-based Progressive 3D Point Set Upsampling " In 2019 CVPR 164 | 165 | * **L2S**: Oren Dovrat, et al. "Learning to Sample" In 2019 CVPR 166 | 167 | * **PCC**: Xuelin Chen, et al. "Unpaired Point Cloud Completion on Real Scans using Adversarial Training" arXiv:1904.00069 168 | 169 | * **PointConv**: Wenxuan Wu, et al. "PointConv: Deep Convolutional Networks on 3D Point Clouds". In 2019 CVPR 170 | 171 | * **PointCNN**: Yangyan Li, et al. "PointCNN: Convolution On X-Transformed Points". In 2018 NIPS 172 | 173 | * **PointWeb**: Hengshuang Zhao, et al. "PointWeb: Enhancing Local Neighborhood Features for Point Cloud Processing" In 2019 CVPR 174 | 175 | * **Point-Capsule**: Yongheng Zhao, et al. "3D Point-Capsule Networks" arXiv:1812.10775 176 | 177 | * **CPL**: Ehsan Nezhadarya, et al. "Adaptive Hierarchical Down-Sampling for Point Cloud Classification" arXiv:1904.08506 178 | 179 | * **PCAN**: Wenxiao Zhang, et al. "PCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval" In 2019 CVPR 180 | 181 | * **PN_VLAD**: Mikaela Angelina Uy, et al. "PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition" In 2018 CVPR 182 | 183 | * **RS-CNN**: Yongcheng Liu, et al. "Relation-Shape Convolutional Neural Network for Point Cloud Analysis" In 2019 CVPR 184 | 185 | * **GPC**: Chong Xiang, et al. "Generating 3D Adversarial Point Clouds" In 2019 CVPR 186 | 187 | * **SO-NET**: Jiaxin Li, et al. "SO-Net: Self-Organizing Network for Point Cloud Analysis" In 2018 CVPR 188 | 189 | * **PU-Net**: Lequan Yu, et al. "PU-Net: Point Cloud Upsampling Network" In 2018 CVPR 190 | 191 | * **EC-Net**: Lequan Yu, et al. "EC-Net: an Edge-aware Point set Consolidation Network" In 2018 ECCV 192 | 193 | * **LSGC**: Chu Wang, et al. "Local Spectral Graph Convolution for Point Set Feature Learning" In 2018 ECCV 194 | 195 | * **Gconv**: Diego Valsesia, et al. " Learning Localized Generative Models for 3D Point Clouds via Graph Convolution" In 2019 ICLR 196 | 197 | * **Scan2Mesh**: Angela Dai, et al. "Scan2Mesh: From Unstructured Range Scans to 3D Meshes." In 2019 CVPR 198 | 199 | * **ContrastNet**: Ling Zhang, et al. "Unsupervised Feature Learning for Point Cloud by Contrasting and Clustering With Graph Convolutional Neural Network" arXiv:1904.12359 200 | 201 | * **VoteNet**: Charles R. Qi, et al. "Deep Hough Voting for 3D Object Detection in Point Clouds" In ICCV 2019 202 | 203 | * **StructureNet**: Zhidong Liang, et al. "3D Graph Embedding Learning with a Structure-aware Loss Function for Point Cloud Semantic Instance Segmentation" arXiv:1902.05247 204 | 205 | * **DeepGCN**: Guohao Li, et al. "Can GCNs Go as Deep as CNNs?" arXiv:1904.03751 206 | 207 | * **RGCNN**: Gusi Te, et al. "RGCNN: Regularized Graph CNN for Point Cloud Segmentation" In 2018 ACM MM 208 | 209 | * **SRN**: Yueqi Duan, et al. "Structural Relational Reasoning of Point Clouds" In 2019 CVPR 210 | 211 | * **Tree-GAN**: Dong Wook Shu, et al. "3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions" arXiv:1905.06292 212 | 213 | * **KPConv**: Hugues Thomas, et al. “KPConv: Flexible and Deformable Convolution for Point Clouds” In ICCV 2019 214 | 215 | * **PointWise**:Matan Shoef, et al. "PointWise: An Unsupervised Point-wise Feature Learning Network" arXiv:1901.04544 216 | 217 | * **GAPNet**: Can Chen, et al. "GAPNet: Graph Attention based Point Neural Network for Exploiting Local Feature of Point Cloud" arXiv:1905.08705 218 | 219 | * **GACNet**: Lei Wang, et al. "Graph Attention Convolution for Point Cloud Segmentation" In CVPR 2019 220 | 221 | * **DensePCR**: Priyanka Mandikal, et al. "Dense 3D Point Cloud Reconstruction Using a Deep Pyramid Network" arXiv:1901.08906 222 | 223 | * **G-NPC**: Xianzhi Li, et al. "Non-Local Low-Rank Normal Filtering for Mesh Denoising" In 2018 PG 224 | 225 | * **AGCN**: Zhuyang Xie, et al. "Point Clouds Learning with Attention-based Graph Convolution Networks" arXiv: 1905.13445 226 | 227 | * **MeshNet**: Yutong Feng, et al. "MeshNet: Mesh Neural Network for 3D Shape Representation" arXiv: 1811.11424 228 | 229 | * **TopNet**: Lyne P. Tchapmi et al."TopNet: Structural Point Cloud Decoder." In CVPR 2019 230 | 231 | * **Nesti-Net**: Yizhak Ben-Shabat et al."Nesti-Net: Normal Estimation for Unstructured 3D Point Clouds using Convolutional Neural Networks." In CVPR 2019 232 | 233 | * **LOGAN**: Kangxue Yin et al."LOGAN: Unpaired Shape Transform in Latent Overcomplete Space." In Siggraph Asia 2019 234 | 235 | * **PointFlow**: Guandao Yang et al. "PointFlow : 3D Point Cloud Generation with Continuous Normalizing Flow" In ICCV 2019 236 | 237 | * **InterpCNN**: Jiageng Mao et al. "Interpolated Convolutional Networks for 3D Point Cloud Understanding" In ICCV 2019 238 | 239 | * **Point-Edge**: Li Jiang et al. "Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation" In ICCV 2019 240 | 241 | * **RI-Conv**: Zhiyuan Zhang et al. "Rotation Invariant Convolutions for 3D Point Clouds Deep Learning" In CVPR 2019 242 | 243 | * **Shape Unicode**: Sanjeev Muralikrishnan et al. "Shape Unicode: A Unified Shape Representation" In CVPR 2019 244 | 245 | * **BPS**: Sergey Prokudin et al. "Efficient Learning on Point Clouds with Basis Point Sets." In ICCV 2019 246 | 247 | * **ShellNet**: Zhiyuan Zhang et al. "ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics." In ICCV 2019 248 | 249 | * **SS-NET**: Jonathan Sauder et al."Self-Supervised Deep Learning on Point Clouds by Reconstructing Space." In NIPS 2019 250 | 251 | * **Attentional EdgeConv**: Qiu Shi et al."Geometric Feedback Network for Point Cloud Classification." arXiv preprint arXiv:1911.12885 (2019). 252 | 253 | * **Morphing-Net**: Minghua Liu et al."Morphing and Sampling Network for Dense Point Cloud Completion." In AAAI 2020 254 | 255 | * **PCC-GAN**: Xuelin Chen et al."Unpaired Point Cloud Completion on Real Scans using Adversarial Training." In ICML 2019. 256 | 257 | * **Point2Node**: Wenkai Han et al."Point2Node: Correlation Learning of Dynamic-Node for Point Cloud Feature Modeling." arXiv preprint arXiv:1912.10775 (2019). 258 | 259 | * **GS-Net**: Mingye Xu et al."Geometry Sharing Network for 3D Point Cloud Classification and Segmentation." In AAAI 2020. 260 | 261 | 262 | ## 2D Image 263 | 264 | * **IMCL**:Dat el al. Interactive Multi-Label CNN Learning with Partial Labels. CVPR 2020. 265 | 266 | * **PISE**:Jinsong Zhang et al. "PISE: Person Image Synthesis and Editing with Decoupled GAN" Tianjin University. CVPR 20201 267 | 268 | * **Im2Vec**:Pradyumna Reddy et al. "Im2Vec: Synthesizing Vector Graphics without Vector Supervision" UCL. CVPR 20201 269 | 270 | * **Infinite Nature**:Andrew Liu et al. "Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Image" Google. arxiv 2021 271 | 272 | * **AniGAN**:Bing Li et al. " AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation" KAUST. arxiv 2021 273 | 274 | * **CS-DisMo**:Xuanchi Ren et al. "Rethinking Content and Style: Exploring Bias for Unsupervised Disentanglemen" HKUST. arxiv 2021 275 | 276 | * **DSA**: Bo Zhao et al. "Dataset Condensation with Differentiable Siamese Augmentation". University of Edinburgh. ICML 2021 277 | 278 | * **DiffAug**: Shengyu Zhao et al. "Differentiable Augmentation for Data-Efficient GAN Training". THU. 2020 NIPS 279 | 280 | * **Deformable DETR**: Xizhou Zhu et al."Deformable DETR: Deformable Transformers for End-to-End Object Detection". SenseTime. 2021 ICLR. 281 | 282 | * **TransGAN**: Yifan Jiang et al. "TransGAN: Two Transformers Can Make One Strong GAN". Texas University. 2021 ICML. 283 | 284 | * **ViT**: Alexey, Dosovitskiy et al. "An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale". Google Brain. 2021 ICLR. 285 | 286 | * **iGPT**: Alec Radford, et al. "Generative Pretraining From Pixels". OpenAI. 2020 ICML. 287 | 288 | * **OASIS**: Edgar Schonfeld, et al. "You Only Need Adversarial Supervision for Semantic Image Synthesis." BOSCH. 2021 ICLR. 289 | 290 | * **U-Net GAN**: Edgar Schonfeld, et al. "A U-Net Based Discriminator for Generative Adversarial Networks." BOSCH. 2020 CVPR. 291 | 292 | * **GauGAN/SPADE**: Taesung Park, et al."Semantic Image Synthesis with Spatially-Adaptive Normalization" NVIDIA. 2019 CVPR. 293 | 294 | * **BigGAN**: Andrew Brock, et al. "Large Scale GAN Training for High Fidelity Natural Image Synthesis" DeepMind. ICLR 2019 295 | 296 | * **Few-Shot StyleGAN**: Tero Karras, et al. "Training generative adversarial networks with limited data." NVIDIA. arXiv:2006.06676. 297 | 298 | * **Semi-StyleGAN**: Tero Karras, et al. "Semi-Supervised StyleGAN for Disentanglement Learning." NVIDIA. 2020 ICML. 299 | 300 | * **StyleGAN2**: Tero Karras, et al. "Analyzing and Improving the Image Quality of StyleGAN." NVIDIA. 2020 CVPR. 301 | 302 | * **StyleGAN**: Tero Karras , et al. "A Style-Based Generator Architecture for Generative Adversarial Networks ." NVIDIA. 2019 CVPR. 303 | 304 | * **Tangent Images**: Marc Eder et al. "Tangent Images for Mitigating Spherical Distortion" CVPR 2020 (UNC) 305 | 306 | * **iSeeBetter**: Aman Chadha et al. "iSeeBetter: Spatio-temporal video super-resolution using recurrent generative back-projection networks" (Standford) 307 | 308 | * **Triplet Attention**: Diganta Misra et al. "Rotate to Attend: Convolutional Triplet Attention Module" arXiv 2010.03045(Landskape) 309 | 310 | * **SSN**: Wenqi Shao et al. "SSN: Learning Sparse Switchable Normalization via SparsestMax" CVPR 2019 (CUHK) 311 | 312 | * **SAOL**: Ildoo Kim et al. "Spatially Attentive Output Layer for Image Classification" CVPR 2020 (Kakao Brain) 313 | 314 | * **IOFPL**: Markus Hofinger et al. "Improving Optical Flow on a Pyramid Level" ECCV 2020 (Facebook) 315 | 316 | * **RAFT**: Zachary Teed et al. "RAFT: Recurrent All-Pairs Field Transforms for Optical Flow" ECCV 2020 (Princeton University) 317 | 318 | * **Shape Adaptor**: Shikun Liu et al."Shape Adaptor: A Learnable Resizing Module". ECCV 2020 (Imperial College London) 319 | 320 | * **FONTS**: David Stutz et al."Disentangling Adversarial Robustness and Generalization" CVPR2019(University of Tubingen) 321 | 322 | * **TI-FGSM**: Yinpeng Dong et al."Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks" CVPR2019(THU) 323 | 324 | * **CUT**: Taesung Park et al."Contrastive Learning for Unpaired Image-to-Image Translation" ECCV2020(UCB) 325 | 326 | * **GAN Prior**: Jinjin Gu et al. "Image Processing Using Multi-Code GAN Prior". CVPR2020(CUHK) 327 | 328 | * **PriorGAN**: Shuyang Gu et al. "PriorGAN: Real Data Prior for Generative Adversarial Nets". arXiv 2006.16990 (USTC) 329 | 330 | * **PULSE**: Sachit Menon et al. "PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models". CVPR2020(Duke) 331 | 332 | * **Relation-Net**: Han Hu et al. "Relation networks for object detection". CVPR 2018(MSRA) 333 | 334 | * **Stand-Alone**: Prajit Ramachandran et al. "Stand-Alone Self-Attention in Vision Models" In NIPS 2019 (Google) 335 | 336 | * **AA-Net**: Irwan Bello et al. "Attention Augmented Convolutional Networks" In ICCV 2019 (Google) 337 | 338 | * **ISRN**: Yuqing Liu et al. "Iterative Network for Image Super-Resolution" arXiv: 2005.09964 (DLUT) 339 | 340 | * **VAE+Flow**: Xuezhe Ma1 et al. "Decoupling Global and Local Representations from/for Image Generation" arXiv: 2004.11820 341 | 342 | * **SAOL**: Ildoo Kim et al. “Spatially Attentive Output Layer for Image Classification." In CVPR 2020 343 | 344 | * **Circle Loss**: Yifan Sun et al."Circle Loss: A Unified Perspective of Pair Similarity Optimization." In CVPR 2020 345 | 346 | * **DeepSnake**: Sida Peng et al."Deep Snake for Real-Time Instance Segmentation." In CVPR 2020 347 | 348 | * **DRN**: Guo, Yong, et al. "Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution." In CVPR 2020. 349 | 350 | * **MSG-GAN**: Animesh Karnewar, et al. "MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks." In CVPR 2020. 351 | 352 | * **StructuredGAN**: Irad Peleg, et al. "Structured GANs." arXiv:2001.05216. 353 | 354 | * **GAN**: Goodfellow, Ian, et al. "Generative adversarial nets." In 2014 NIPS . 355 | 356 | * **cGAN**: Mirza, Mehdi, and Simon Osindero. "Conditional generative adversarial nets." arXiv preprint arXiv:1411.1784 (2014). 357 | 358 | * **S2-GAN**: Xiaolong Wang, et al. "Generative Image Modeling using Style and Structure Adversarial Networks." In 2016 ECCV 359 | 360 | * **DCGAN**: Radford, et al.. "Unsupervised representation learning with deep convolutional generative adversarial networks." In 2016 ICLR 361 | 362 | * **Pixel2Pixel**: Isola, Phillip, et al. "Image-to-image translation with conditional adversarial networks." In 2017 CVPR 363 | 364 | * **SRGAN**: Christian,Ledig, et al. "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network." In 2017 CVPR. 365 | 366 | * **AdaIN**: Xun Huang , et al. "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization ." In 2017 ICCV 367 | 368 | * **CycleGAN**：Zhu, Jun-Yan, et al. "Unpaired image-to-image translation using cycle-consistent adversarial networks." In 2017 ICCV. 369 | 370 | * **BicycleGAN**：Zhu, Jun-Yan, et al. "Toward Multimodal Image-to-Image Translation." In 2017 NIPS. 371 | 372 | * **Least square loss** :Xudong, Mao , et al. "Least Squares Generative Adversarial Networks ." In 2017 ICCV. 373 | 374 | * **StackGAN**: Han Zhang, et al. "StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks ." In 2017 ICCV. 375 | 376 | * **StackGAN++**: Han Zhang, et al. "StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks ." In 2018 TPAMI. 377 | 378 | * **TTUR**: Martin Heusel, et al. "GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium ." In 2017 NIPS. 379 | 380 | * **SGAN**: Xun Huang , et al. "Stacked Generative Adversarial Networks ." In 2017 CVPR. 381 | 382 | * **StarGAN**: Choi, Yunjey, et al. "Stargan: Unified generative adversarial networks for multi-domain image-to-image translation." In CVPR 2018. 383 | 384 | * **DISSECTIONGAN**: Zhu, Jun-Yan, et al. "GAN DISSECTION: VISUALIZING AND UNDERSTANDING GENERATIVE ADVERSARIAL NETWORKS ." arXiv:1811.10597. 385 | 386 | * **GDWTC**: Wonwoong Cho, et al. "Image-to-Image Translation via Group-wise Deep Whitening and Coloring Transformation" arXiv:1812.09912. 387 | 388 | * **Latent Filter GAN**: Yazeed Alharbi, et al."Latent Filter Scaling for Multimodal Unsupervised Image-to-Image Translation." In CVPR 2019. 389 | 390 | * **CariGAN**: KAIDI CAO, et al. "CariGANs: Unpaired Photo-to-Caricature Translation." In 2018 Siggraph. 391 | 392 | * **AttnGAN**: Tao Xu, et al. "AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks." In 2018 CVPR 393 | 394 | * **Pixel2PixelHD**: Ting-Chun Wang, et al. "High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs." In 2018 CVPR 395 | 396 | * **Attention-GAN**: Xinyuan Chen, et al. "Attention-GAN for Object Transfiguration in Wild Images." In 2018 ECCV 397 | 398 | * **DRIT**: Hsin-Ying Lee, et al. "Diverse Image-to-Image Translation via Disentangled Representations." In 2018 ECCV 399 | 400 | * **Contextual GAN**: Yongyi Lu, et al. "Image Generation from Sketch Constraint Using Contextual GAN." In 2018 ECCV 401 | 402 | * **MUINT**: Xun Huang, et al. "Multimodal Unsupervised Image-to-Image Translation" In 2018 ECCV 403 | 404 | * **Recycle-GAN**: Aayush Bansal , et al. "Recycle-GAN: Unsupervised Video Retargeting" In 2018 ECCV 405 | 406 | * **Sub-GAN**: Jie Liang, et al."Sub-GAN: An Unsupervised Generative Model via Subspaces" In 2018 ECCV 407 | 408 | * **Stack CycleGAN**:Minjun Li, et al. "Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks " In 2018 ECCV 409 | 410 | * **Progressive GAN**: Tero Karras , et al."PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION" In 2018 ICLR 411 | 412 | * **SAGAN**: Han Zhang, et al. "Self-Attention Generative Adversarial Networks" In 2018 ICLR 413 | 414 | * **SN**: Takeru Miyato, et al. "SPECTRAL NORMALIZATION FOR GENERATIVE ADVERSARIAL NETWORKS " In 2018 ICLR 415 | 416 | * **Augmented CycleGAN**: Amjad Almahairi , et al. "Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data" In 2018 ICML 417 | 418 | * **BigGAN**: Andrew Brock, et al."LARGE SCALE GAN TRAINING FOR HIGH FIDELITY NATURAL IMAGE SYNTHESIS " In ICLR 2019 419 | 420 | * **InstaGAN**: Sangwoo Mo, et al. "INSTANCE-AWARE IMAGE-TO-IMAGE TRANSLATION " In 2019 ICLR 421 | 422 | * **RGAN**: Alexia Jolicoeur-Martineau, et al. "The relativistic discriminator: a key element missing from standard GAN" In 2019 ICLR 423 | 424 | * **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 425 | 426 | * **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 427 | 428 | * **DANet**: Jun Fu et al. "Dual Attention Network for Scene Segmentation." In CVPR 2019 429 | 430 | * **FineGAN**: Krishna Kumar Singh et al. "FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery." In CVPR 2019 431 | 432 | * **TransGaGa**: Wayne Wu et al. "TransGaGa: Geometry-Aware Unsupervised Image-to-Image Translation." In CVPR 2019 433 | 434 | * **Deblur-GAN**: Boyu Lu et al. "Unsupervised Domain-Specific Deblurring via Disentangled Representations." In CVPR 2019 435 | 436 | * **NoiseFlow**: Abdelrahman Abdelhamed et al. "Noise Flow: Noise Modeling with Conditional Normalizing Flows." arXiv:1908.08453 437 | 438 | * **DMIT**: Xiaoming Yu et al. "Multi-mapping Image-to-Image Translation via Learning Disentanglement." In NIPS 2019 439 | 440 | * **Stylized-ImageNet**: Robert Geirhos et al. "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness." In ICLR 2019 441 | 442 | * **InvertGray**: Xia, Menghan et al. "Invertible grayscale." In SIGGRAPH Asia 2018 443 | 444 | * **DegradeSR**: Bulat, Adrian et al. "To learn image super-resolution, use a GAN to learn how to do image degradation first." In ECCV 2018 445 | 446 | ## Network 447 | * **EfficientDet**: Tan, Mingxing et al. "EfficientDet: Scalable and Efficient Object Detection." arXiv: 1911.09070 448 | 449 | * **STDL**: Peng Zhou et al. "Scale-Transferrable Object Detection." In CVPR 2018. 450 | 451 | * **DARTS**: Hanxiao Liu et al. "DARTS: DIFFERENTIABLE ARCHITECTURE SEARCH." In ICLR 2019. (CMU) 452 | 453 | ## GNN 454 | * Peter W. Battaglia, et al. "Relational inductive biases, deep learning, and graph networks." arXiv: 1806.01261 455 | 456 | 457 | ## NLP 458 | 459 | * **Multi Agent** :"MULTI-AGENT DUAL LEARNING" In ICLR 2019 460 | --------------------------------------------------------------------------------