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
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 .