11.2.1.3.13 Point Cloud Generation, Point Cloud Synthesis

Chapter Contents (Back)
Synthesis. Point Cloud Generation. Point Cloud Synthesis. Text to Depth. Not directly from the scanners.
See also Adversarial Networks for Image Synthesis, Image Generation.
See also Laser Sensors for Range, Time of Flight.

Xia, Y.[Yan], Wang, C.[Cheng], Xu, Y.S.[Yu-Sheng], Zang, Y.[Yu], Liu, W.Q.[Wei-Quan], Li, J.[Jonathan], Stilla, U.[Uwe],
RealPoint3D: Generating 3D Point Clouds from a Single Image of Complex Scenarios,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Luo, N.[Nan], Huang, L.[Ling], Wang, Q.[Quan], Liu, G.[Gang],
An Improved Algorithm Robust to Illumination Variations for Reconstructing Point Cloud Models from Images,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Zhou, T.[Tian], Hasheminasab, S.M.[Seyyed Meghdad], Habib, A.[Ayman],
Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems,
PandRS(180), 2021, pp. 336-356.
Elsevier DOI 2109
Camera/LiDAR integration, Bundle adjustment, Unmanned aerial vehicles, Structure from motion, System calibration BibRef

Tian, Y.L.[Yong-Lin], Wang, X.[Xiao], Shen, Y.[Yu], Guo, Z.Z.[Zhong-Zheng], Wang, Z.L.[Zi-Lei], Wang, F.Y.[Fei-Yue],
Parallel Point Clouds: Hybrid Point Cloud Generation and 3D Model Enhancement via Virtual-Real Integration,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Li, Y.S.[Yu-Shi], Baciu, G.[George],
HSGAN: Hierarchical Graph Learning for Point Cloud Generation,
IP(30), 2021, pp. 4540-4554.
IEEE DOI 2105
Shape, Training, Convolution, Solid modeling, Semantics, gradient penalty BibRef

Hu, J.[Jiwei], Deng, W.[Wupeng], Liu, Q.[Quan], Lam, K.M.[Kin-Man], Lou, P.[Ping],
Constructing an efficient and adaptive learning model for 3D object generation,
IET-IPR(15), No. 8, 2021, pp. 1745-1758.
DOI Link 2106
GAN for point cloud synthesis. BibRef

Zhang, R.N.[Ruo-Nan], Chen, J.Y.[Jing-Yi], Gao, W.[Wei], Li, G.[Ge], Li, T.H.[Thomas H.],
PointOT: Interpretable Geometry-Inspired Point Cloud Generative Model via Optimal Transport,
CirSysVideo(32), No. 10, October 2022, pp. 6792-6806.
IEEE DOI 2210
Point cloud compression, Transportation, Manifolds, Computational modeling, Task analysis, Probability distribution, auto-encoder BibRef

Triess, L.T.[Larissa T.], Rist, C.B.[Christoph B.], Peter, D.[David], Zöllner, J.M.[J. Marius],
A Realism Metric for Generated LiDAR Point Clouds,
IJCV(130), No. 12, December 2022, pp. 2962-2979.
Springer DOI 2211
Quality of the generated data. BibRef

Wen, Y.X.[Yu-Xin], Lin, J.H.[Jie-Hong], Chen, K.[Ke], Chen, C.L.P.[C. L. Philip], Jia, K.[Kui],
Geometry-Aware Generation of Adversarial Point Clouds,
PAMI(44), No. 6, June 2022, pp. 2984-2999.
IEEE DOI 2205
Extend defense to 3D. Shape, Image reconstruction, Surface reconstruction, object surface geometry BibRef

Liang, Q.[Qi], Li, Q.[Qiang], Yang, S.[Song],
LP-GAN: Learning perturbations based on generative adversarial networks for point cloud adversarial attacks,
IVC(120), 2022, pp. 104370.
Elsevier DOI 2204
3D model, Point cloud, Adversarial attack, GAN, BibRef

Kimura, T.[Takumi], Matsubara, T.[Takashi], Uehara, K.[Kuniaki],
Topology-Aware Flow-Based Point Cloud Generation,
CirSysVideo(32), No. 11, November 2022, pp. 7967-7982.
IEEE DOI 2211
Point cloud compression, Neural networks, Manifolds, Semantics, Numerical models, Topology, Shape, Deep learning, generative model, point clouds BibRef

Zhang, H.Q.[Han-Qing], Lin, Y.[Yun], Teng, F.[Fei], Hong, W.[Wen],
A Probabilistic Approach for Stereo 3D Point Cloud Reconstruction from Airborne Single-Channel Multi-Aspect SAR Image Sequences,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Spurek, P.[Przemyslaw], Zieba, M.[Maciej], Tabor, J.[Jacek], Trzcinski, T.[Tomasz],
General Hypernetwork Framework for Creating 3D Point Clouds,
PAMI(44), No. 12, December 2022, pp. 9995-10008.
IEEE DOI 2212
Solid modeling, Shape, Training, Probability distribution, Numerical models, Transforms, Hypernetworks, generative modeling BibRef

Li, P.P.[Pei-Pei], Liu, X.[Xiyan], Huang, J.Z.[Ji-Zhou], Xia, D.[Deguo], Yang, J.Z.[Jian-Zhong], Lu, Z.[Zhen],
Progressive generation of 3D point clouds with hierarchical consistency,
PR(136), 2023, pp. 109200.
Elsevier DOI 2301
3D Point cloud generation, Point cloud analysis, Generative adversarial networks, Variational autoencoder, Hierarchical consistency BibRef

Jiang, N.[Nan], Sheng, B.[Bin], Li, P.[Ping], Lee, T.Y.[Tong-Yee],
PhotoHelper: Portrait Photographing Guidance Via Deep Feature Retrieval and Fusion,
MultMed(25), 2023, pp. 2226-2238.
IEEE DOI 2306
Feature extraction, Image color analysis, Neural networks, Visualization, Real-time systems, Deep learning, Task analysis, spatial composition rule BibRef

Lu, Y.[Yue], Guo, C.[Chao], Dai, X.Y.[Xing-Yuan], Wang, F.Y.[Fei-Yue],
Generating Emotion Descriptions for Fine Art Paintings Via Multiple Painting Representations,
IEEE_Int_Sys(38), No. 3, May 2023, pp. 31-40.
IEEE DOI 2307
Painting, Feature extraction, Emotion recognition, Detectors, Intelligent systems, Convolutional neural networks, Art BibRef

Mandal, M.[Maniratnam], Ghadiyaram, D.[Deepti], Gurari, D.[Danna], Bovik, A.C.[Alan C.],
Helping Visually Impaired People Take Better Quality Pictures,
IP(32), 2023, pp. 3873-3884.
IEEE DOI 2307
Distortion, Predictive models, Image quality, Social networking (online), Data models, Visualization, human study BibRef

Wang, E.[Ende], Sun, H.[Hui], Wang, B.[Bing], Cao, Z.[Zhiyu], Liu, Z.Y.[Zhi-Yuan],
3D-FEGNet: A feature enhanced point cloud generation network from a single image,
IET-CV(17), No. 1, 2023, pp. 98-110.
DOI Link 2303
3D Single-view reconstruction, point cloud, point cloud pyramid BibRef

Li, L.[Leida], Zhu, T.[Tong], Chen, P.F.[Peng-Fei], Yang, Y.Z.[Yu-Zhe], Li, Y.Q.[Ya-Qian], Lin, W.S.[Wei-Si],
Image Aesthetics Assessment with Attribute-Assisted Multimodal Memory Network,
CirSysVideo(33), No. 12, December 2023, pp. 7413-7424.
IEEE DOI Code:
WWW Link. 2312
BibRef

Yang, Z.C.[Zhi-Chao], Li, L.[Leida], Yang, Y.Z.[Yu-Zhe], Li, Y.Q.[Ya-Qian], Lin, W.S.[Wei-Si],
Multi-Level Transitional Contrast Learning for Personalized Image Aesthetics Assessment,
MultMed(26), 2024, pp. 1944-1956.
IEEE DOI 2402
Task analysis, Feature extraction, Databases, Standards, Videos, Training, aesthetic preferences BibRef

Lan, G.P.[Gui-Peng], Xiao, S.[Shuai], Yang, J.C.[Jia-Chen], Zhou, Y.S.[Yan-Shuang], Wen, J.[Jiabao], Lu, W.[Wen], Gao, X.B.[Xin-Bo],
Image Aesthetics Assessment Based on Hypernetwork of Emotion Fusion,
MultMed(26), 2024, pp. 3640-3650.
IEEE DOI 2402
Task analysis, Visualization, Transformers, Semantics, Feature extraction, Psychology, Videos, image emotion BibRef


Luo, S.[Simian], Qian, X.[Xuelin], Fu, Y.W.[Yan-Wei], Zhang, Y.[Yinda], Tai, Y.[Ying], Zhang, Z.Y.[Zhen-Yu], Wang, C.J.[Cheng-Jie], Xue, X.Y.[Xiang-Yang],
Learning Versatile 3D Shape Generation with Improved Auto-regressive Models,
ICCV23(14093-14103)
IEEE DOI 2401
BibRef

Manivasagam, S.[Sivabalan], Bârsan, I.A.[Ioan Andrei], Wang, J.K.[Jing-Kang], Yang, Z.[Ze], Urtasun, R.[Raquel],
Towards Zero Domain Gap: A Comprehensive Study of Realistic LiDAR Simulation for Autonomy Testing,
ICCV23(8238-8248)
IEEE DOI Code:
WWW Link. 2401
BibRef

Sargent, K.[Kyle], Koh, J.Y.[Jing Yu], Zhang, H.[Han], Chang, H.[Huiwen], Herrmann, C.[Charles], Srinivasan, P.[Pratul], Wu, J.J.[Jia-Jun], Sun, D.Q.[De-Qing],
VQ3D: Learning a 3D-Aware Generative Model on ImageNet,
ICCV23(4217-4227)
IEEE DOI 2401
BibRef

Li, S.J.[Shi-Jie], Li, R.[Rong], Gall, J.[Juergen],
Semantic RGB-D Image Synthesis,
LIMIT23(944-952)
IEEE DOI 2401
BibRef

Tian, X.[Xi], Yang, Y.L.[Yong-Liang], Wu, Q.[Qi],
ShapeScaffolder: Structure-Aware 3D Shape Generation from Text,
ICCV23(2715-2724)
IEEE DOI 2401
BibRef

Wu, Z.J.[Zi-Jie], Wang, Y.[Yaonan], Feng, M.[Mingtao], Xie, H.[He], Mian, A.[Ajmal],
Sketch and Text Guided Diffusion Model for Colored Point Cloud Generation,
ICCV23(8895-8905)
IEEE DOI 2401
BibRef

Zhu, Z.[Zhe], Chen, H.H.[Hong-Hua], He, X.[Xing], Wang, W.M.[Wei-Ming], Qin, J.[Jing], Wei, M.Q.[Ming-Qiang],
SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator,
ICCV23(14462-14472)
IEEE DOI Code:
WWW Link. 2401
BibRef

Nakayama, G.K.[George Kiyohiro], Uy, M.A.[Mikaela Angelina], Huang, J.[Jiahui], Hu, S.M.[Shi-Min], Li, K.[Ke], Guibas, L.J.[Leonidas J.],
DiffFacto: Controllable Part-Based 3D Point Cloud Generation with Cross Diffusion,
ICCV23(14211-14221)
IEEE DOI Code:
WWW Link. 2401
BibRef

Suárez, P.L.[Patricia L.], Carpio, D.[Dario], Sappa, A.[Angel],
A Deep Learning Based Approach for Synthesizing Realistic Depth Maps,
CIAP23(II:369-380).
Springer DOI 2312
BibRef

Apostolidis, E.[Evlampios], Balaouras, G.[Georgios], Mezaris, V.[Vasileios], Patras, I.[Ioannis],
Selecting A Diverse Set Of Aesthetically-Pleasing and Representative Video Thumbnails Using Reinforcement Learning,
ICIP23(2460-2464)
IEEE DOI 2312
BibRef

Yi, H.W.[Hong-Wei], Huang, C.H.P.[Chun-Hao P.], Tripathi, S.[Shashank], Hering, L.[Lea], Thies, J.[Justus], Black, M.J.[Michael J.],
MIME: Human-Aware 3D Scene Generation,
CVPR23(12965-12976)
IEEE DOI 2309

WWW Link. BibRef

Ibing, M.[Moritz], Kobsik, G.[Gregor], Kobbelt, L.[Leif],
Octree Transformer: Autoregressive 3D Shape Generation on Hierarchically Structured Sequences,
StruCo3D23(2698-2707)
IEEE DOI 2309
BibRef

Huang, S.Y.[Si-Yuan], Wang, Z.[Zan], Li, P.[Puhao], Jia, B.X.[Bao-Xiong], Liu, T.Y.[Teng-Yu], Zhu, Y.X.[Yi-Xin], Liang, W.[Wei], Zhu, S.C.[Song-Chun],
Diffusion-based Generation, Optimization, and Planning in 3D Scenes,
CVPR23(16750-16761)
IEEE DOI 2309
BibRef

Yang, Z.[Zhulun], Chen, Y.J.[Yi-Jun], Zheng, X.W.[Xian-Wei], Chang, Y.D.[Ya-Dong], Li, X.[Xutao],
Conditional GAN for Point Cloud Generation,
ACCV22(VII:117-133).
Springer DOI 2307
BibRef

Nakashima, K.[Kazuto], Iwashita, Y.[Yumi], Kurazume, R.[Ryo],
Generative Range Imaging for Learning Scene Priors of 3D LiDAR Data,
WACV23(1256-1266)
IEEE DOI 2302
Training, Adaptation models, Laser radar, Semantic segmentation, Imaging, Rendering (computer graphics), Applications: Robotics, 3D computer vision BibRef

Kim, J.Y.[Jae-Yeon], Hua, B.S.[Binh-Son], Nguyen, D.T.[Duc Thanh], Yeung, S.K.[Sai-Kit],
PointInverter: Point Cloud Reconstruction and Editing via a Generative Model with Shape Priors,
WACV23(592-601)
IEEE DOI 2302
Point cloud compression, Solid modeling, Codes, Shape, Generative adversarial networks, Algorithms: 3D computer vision BibRef

Ghosal, K.[Koustav], Smolic, A.[Aljosa],
Image Aesthetics Assessment Using Graph Attention Network,
ICPR22(3160-3167)
IEEE DOI 2212
Convolutional codes, Training, Visualization, Layout, Semantics, Feature extraction, Graph neural networks BibRef

Umam, A.[Ardian], Yang, C.K.[Cheng-Kun], Chuang, Y.Y.[Yung-Yu], Chuang, J.H.[Jen-Hui], Lin, Y.Y.[Yen-Yu],
Point MixSwap: Attentional Point Cloud Mixing via Swapping Matched Structural Divisions,
ECCV22(XXIX:596-611).
Springer DOI 2211

WWW Link. Point cloud augmentation. BibRef

Weng, X.S.[Xin-Shuo], Nan, J.Y.[Jun-Yu], Lee, K.H.[Kuan-Hui], McAllister, R.[Rowan], Gaidon, A.[Adrien], Rhinehart, N.[Nicholas], Kitani, K.M.[Kris M.],
S2Net: Stochastic Sequential Pointcloud Forecasting,
ECCV22(XXVII:549-564).
Springer DOI 2211
BibRef

Zyrianov, V.[Vlas], Zhu, X.[Xiyue], Wang, S.[Shenlong],
Learning to Generate Realistic LiDAR Point Clouds,
ECCV22(XXIII:17-35).
Springer DOI 2211
BibRef

Chen, Y.W.[Yong-Wei], Wang, Z.[Zihao], Zou, L.[Longkun], Chen, K.[Ke], Jia, K.[Kui],
Quasi-Balanced Self-Training on Noise-Aware Synthesis of Object Point Clouds for Closing Domain Gap,
ECCV22(XXXIII:728-745).
Springer DOI 2211
BibRef

Huang, Q.D.[Qi-Dong], Dong, X.Y.[Xiao-Yi], Chen, D.D.[Dong-Dong], Zhou, H.[Hang], Zhang, W.M.[Wei-Ming], Yu, N.H.[Neng-Hai],
Shape-invariant 3D Adversarial Point Clouds,
CVPR22(15314-15323)
IEEE DOI 2210
Point cloud compression, Resistance, Solid modeling, Sensitivity, Shape, Adversarial attack and defense, Recognition: detection, retrieval BibRef

Chen, J.Y.[Jing-Yi], Li, G.[Ge], Zhang, R.N.[Ruo-Nan], Li, T.H.[Thomas H.], Gao, W.[Wei],
Pointivae: Invertible Variational Autoencoder Framework for 3D Point Cloud Generation,
ICIP22(3216-3220)
IEEE DOI 2211
Point cloud compression, Couplings, Codes, Shape, Aggregates, Decoding, Point cloud, local feature, VAE, generating capability, autoencoding BibRef

Tang, Y.Z.[Ying-Zhi], Qian, Y.[Yue], Zhang, Q.J.[Qi-Jian], Zeng, Y.M.[Yi-Ming], Hou, J.H.[Jun-Hui], Zhe, X.F.[Xue-Fei],
WarpingGAN: Warping Multiple Uniform Priors for Adversarial 3D Point Cloud Generation,
CVPR22(6387-6395)
IEEE DOI 2210
Point cloud compression, Measurement, Training, Visualization, Codes, 3D from multi-view and sensors, Image and video synthesis and generation BibRef

Zhang, J.Y.[Jing-Yu], Jiang, C.H.[Chun-Hua], Wang, X.P.[Xu-Peng], Cai, M.[Mumuxin],
TD-Net: Topology Destruction Network for Generating Adversarial Point Cloud,
ICIP21(3098-3102)
IEEE DOI 2201
Solid modeling, Image recognition, Network topology, Topology, Decoding, adversarial point clouds, generative network, point cloud topology BibRef

Wen, C.[Cheng], Yu, B.S.[Bao-Sheng], Tao, D.C.[Da-Cheng],
Learning Progressive Point Embeddings for 3D Point Cloud Generation,
CVPR21(10261-10270)
IEEE DOI 2111
Deep learning, Solid modeling, Generators, Pattern recognition BibRef

Luo, S.T.[Shi-Tong], Hu, W.[Wei],
Diffusion Probabilistic Models for 3D Point Cloud Generation,
CVPR21(2836-2844)
IEEE DOI 2111
Training, Thermodynamics, Solid modeling, Shape, Diffusion processes, Transforms BibRef

Hu, T.[Tao], Lin, G.[Geng], Han, Z.Z.[Zhi-Zhong], Zwicker, M.[Matthias],
Learning to Generate Dense Point Clouds with Textures on Multiple Categories,
WACV21(2169-2178)
IEEE DOI 2106
Geometry, Shape, Pipelines, Reconstruction algorithms, Topology BibRef

Mo, K.C.[Kai-Chun], Wang, H.[He], Yan, X.C.[Xin-Chen], Guibas, L.J.[Leonidas J.],
Pt2pc: Learning to Generate 3d Point Cloud Shapes from Part Tree Conditions,
ECCV20(VI:683-701).
Springer DOI 2011
BibRef

Sun, Y.B.[Yong-Bin], Wang, Y.[Yue], Liu, Z.W.[Zi-Wei], Siegel, J.E.[Joshua E.], Sarma, S.E.[Sanjay E.],
PointGrow: Autoregressively Learned Point Cloud Generation with Self-Attention,
WACV20(61-70)
IEEE DOI 2006
Shape, Solid modeling, Measurement, Context-aware services, Frequency modulation, Semantics BibRef

Hamdi, A.[Abdullah], Rojas, S.[Sara], Thabet, A.[Ali], Ghanem, B.[Bernard],
Advpc: Transferable Adversarial Perturbations on 3d Point Clouds,
ECCV20(XII: 241-257).
Springer DOI 2010
BibRef

Tchapmi, L.P.[Lyne P.], Kosaraju, V.[Vineet], Rezatofighi, H.[Hamid], Reid, I.D.[Ian D.], Savarese, S.[Silvio],
TopNet: Structural Point Cloud Decoder,
CVPR19(383-392).
IEEE DOI 2002
Point cloud generation from models. BibRef

Zainuddin, K., Majid, Z., Ariff, M.F.M., Idris, K.M.,
Measurement Accuracy On 3d Point Cloud Generated Using Multispectral Imagery By Different Calibration Methods,
GGT19(697-703).
DOI Link 1912
BibRef

Shu, D.W.[Dong-Wook], Park, S.W.[Sung Woo], Kwon, J.[Junseok],
3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions,
ICCV19(3858-3867)
IEEE DOI 2004
Generate 3D data. feature extraction, image classification, image matching, object detection, trees (mathematics), BibRef

Mandikal, P.[Priyanka], Navaneet, K.L., Babu, R.V.[R. Venkatesh],
3D-PSRNet: Part Segmented 3D Point Cloud Reconstruction from a Single Image,
3DSemantics18(III:662-674).
Springer DOI 1905
BibRef

Soule, S., Maurice, K., Walcher, W., Szabo, J.,
Advanced point cloud generation for photogrammetric modeling of complex 3D objects,
ICIP02(III: 529-532).
IEEE DOI 0210
BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Visual Sentiment Evaluation .


Last update:Feb 29, 2024 at 09:13:14