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.Y.[Zhi-Yu],
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
Yuan, C.F.[Chao-Feng],
Pan, J.H.[Jing-Hui],
Zhang, Z.X.[Zhao-Xiang],
Qi, M.[Min],
Xu, Y.L.[Yue-Lei],
3D-PCGR: Colored Point Cloud Generation and Reconstruction with
Surface and Scale Constraints,
RS(16), No. 6, 2024, pp. 1004.
DOI Link
2403
BibRef
Yang, D.[Dong],
Wang, J.Y.[Jing-Yuan],
Yang, X.[Xi],
3D Point Cloud Shape Generation with Collaborative Learning of
Generative Adversarial Network and Auto-Encoder,
RS(16), No. 10, 2024, pp. 1772.
DOI Link
2405
BibRef
Zhang, Y.X.[Yu-Xiao],
Ding, M.[Ming],
Yang, H.T.[Han-Ting],
Niu, Y.J.[Ying-Jie],
Ge, M.N.[Mao-Ning],
Ohtani, K.[Kento],
Zhang, C.[Chi],
Takeda, K.[Kazuya],
LiDAR Point Cloud Augmentation for Adverse Conditions Using
Conditional Generative Model,
RS(16), No. 12, 2024, pp. 2247.
DOI Link
2406
BibRef
Kamal, M.[Minhas],
Prabhakaran, B.[Balakrishnan],
Generative AI for 3-D Point Clouds,
MultMedMag(31), No. 2, April 2024, pp. 5-6.
IEEE DOI
2408
BibRef
Xiang, Z.K.[Zheng-Kang],
Huang, Z.X.[Ze-Xian],
Khoshelham, K.[Kourosh],
Synthetic lidar point cloud generation using deep generative models
for improved driving scene object recognition,
IVC(150), 2024, pp. 105207.
Elsevier DOI Code:
WWW Link.
2409
Lidar point cloud, Object recognition, Generative model, Data augmentation
BibRef
Chen, L.M.[Lian-Ming],
Tong, Y.[Yong],
Yang, N.[Ning],
Zuo, Y.P.[Yi-Peng],
Menhas, M.I.[Muhammad Ilyas],
Ahmad, B.[Bilal],
Chen, H.[Hui],
3D-ISRNet: Generating 3D point clouds through image similarity
retrieval in a complex background from a single image,
IVC(150), 2024, pp. 105203.
Elsevier DOI
2409
3D reconstruction, Single image, Complex background, Image similarity retrieval
BibRef
Ahmadi, S.[Sahar],
Cheraghian, A.[Ali],
Chowdhury, T.F.[Townim Faisal],
Saberi, M.[Morteza],
Rahman, S.[Shafin],
3D scene generation for zero-shot learning using ChatGPT guided
language prompts,
CVIU(249), 2024, pp. 104211.
Elsevier DOI Code:
WWW Link.
2412
Zero-shot learning, Deep learning, Point cloud object, Contrastive learning
BibRef
Yuan, Q.[Quan],
Li, L.[Leida],
Chen, P.F.[Peng-Fei],
Aesthetic image cropping meets VLP: Enhancing good while reducing bad,
JVCIR(105), 2024, pp. 104316.
Elsevier DOI
2501
Image cropping, Vision-Language Pre-training, Aesthetic quality assessment
BibRef
Li, W.W.[Wen-Wen],
Chen, Y.X.[Ya-Xing],
Fan, Q.Y.[Qian-Yue],
Yang, M.[Meng],
Guo, B.[Bin],
Yu, Z.W.[Zhi-Wen],
I-PAttnGAN: An Image-Assisted Point Cloud Generation Method Based on
Attention Generative Adversarial Network,
RS(17), No. 1, 2025, pp. 153.
DOI Link
2501
BibRef
Pérez, E.[Emiliano],
Sánchez-Hermosell, A.[Adolfo],
Merchán, P.[Pilar],
TLSynth: A Novel Blender Add-On for Real-Time Point Cloud Generation
from 3D Models,
RS(17), No. 3, 2025, pp. 421.
DOI Link
2502
BibRef
Mo, S.T.[Shen-Tong],
Xie, E.[Enze],
Wu, Y.[Yue],
Chen, J.S.[Jun-Song],
Nießner, M.[Matthias],
Li, Z.G.[Zhen-Guo],
Fast Training of Diffusion Transformer with Extreme Masking for 3d
Point Clouds Generation,
ECCV24(LXXXIV: 354-370).
Springer DOI
2412
BibRef
Hu, Q.J.[Qian-Jiang],
Zhang, Z.M.[Zhi-Min],
Hu, W.[Wei],
Rangeldm: Fast Realistic Lidar Point Cloud Generation,
ECCV24(XLIV: 115-135).
Springer DOI
2412
BibRef
Zhou, C.L.[Chen-Liang],
Zhong, F.[Fangcheng],
Hanji, P.[Param],
Guo, Z.L.[Zhi-Lin],
Fogarty, K.[Kyle],
Sztrajman, A.[Alejandro],
Gao, H.Y.[Hong-Yun],
Oztireli, C.[Cengiz],
Frepolad: Frequency-rectified Point Latent Diffusion for Point Cloud
Generation,
ECCV24(LXVII: 434-453).
Springer DOI
2412
BibRef
Zhai, Y.H.[Yuan-Hao],
Lin, K.[Kevin],
Li, L.J.[Lin-Jie],
Lin, C.C.[Chung-Ching],
Wang, J.F.[Jian-Feng],
Yang, Z.Y.[Zheng-Yuan],
Doermann, D.[David],
Yuan, J.S.[Jun-Song],
Liu, Z.C.[Zi-Cheng],
Wang, L.J.[Li-Juan],
Idol: Unified Dual-modal Latent Diffusion for Human-centric Joint
Video-depth Generation,
ECCV24(XV: 134-152).
Springer DOI
2412
BibRef
Ran, H.X.[Hao-Xi],
Guizilini, V.[Vitor],
Wang, Y.[Yue],
Towards Realistic Scene Generation with LiDAR Diffusion Models,
CVPR24(14738-14748)
IEEE DOI
2410
Geometry, Laser radar, Semantics, Pipelines, Aerospace electronics,
Diffusion models, Controllable LiDAR Generation,
Text-to-LiDAR
BibRef
Wu, Y.[Yang],
Zhang, K.[Kaihua],
Qian, J.J.[Jian-Jun],
Xie, J.[Jin],
Yang, J.[Jian],
Text2LiDAR: Text-guided Lidar Point Cloud Generation via
Equirectangular Transformer,
ECCV24(LVI: 291-310).
Springer DOI
2412
BibRef
Ren, Z.Y.[Zhi-Yuan],
Kim, M.[Minchul],
Liu, F.[Feng],
Liu, X.M.[Xiao-Ming],
TIGER: Time-Varying Denoising Model for 3D Point Cloud Generation
with Diffusion Process,
CVPR24(9462-9471)
IEEE DOI Code:
WWW Link.
2410
Point cloud compression, Solid modeling, Codes, Shape, Convolution,
Noise reduction, Diffusion Model, Point Cloud, ShapeNet,
3D Vision
BibRef
Xu, H.Y.[Hai-Yang],
Lei, Y.[Yu],
Chen, Z.[Zeyuan],
Zhang, X.[Xiang],
Zhao, Y.[Yue],
Wang, Y.L.[Yi-Lin],
Tu, Z.W.[Zhuo-Wen],
Bayesian Diffusion Models for 3D Shape Reconstruction,
CVPR24(10628-10638)
IEEE DOI Code:
WWW Link.
2410
Point cloud compression, Shape, Diffusion processes,
Diffusion models, Prediction algorithms, Bayes methods,
3D Reconstruction
BibRef
Ren, X.[Xuanchi],
Huang, J.[Jiahui],
Zeng, X.H.[Xiao-Hui],
Museth, K.[Ken],
Fidler, S.[Sanja],
Williams, F.[Francis],
XCube: Large-Scale 3D Generative Modeling using Sparse Voxel
Hierarchies,
CVPR24(4209-4219)
IEEE DOI
2410
Solid modeling, Computational modeling, Diffusion models,
Data structures
BibRef
Leng, Z.Y.[Zhi-Ying],
Birdal, T.[Tolga],
Liang, X.H.[Xiao-Hui],
Tombari, F.[Federico],
HyperSDFusion: Bridging Hierarchical Structures in Language and
Geometry for Enhanced 3D Text2Shape Generation,
CVPR24(19691-19700)
IEEE DOI
2410
Geometry, Representation learning, Learning systems,
Technological innovation, Shape, 3D shape generation,
Hyperbolic representaion learning
BibRef
Gao, G.[Gege],
Liu, W.[Weiyang],
Chen, A.[Anpei],
Geiger, A.[Andreas],
Schölkopf, B.[Bernhard],
GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs,
CVPR24(21295-21304)
IEEE DOI
2410
Solid modeling, Grounding, Image edge detection, Text to image,
Manuals, Compositional 3D Generation, 3D Creation from Scene Graph
BibRef
Karnewar, A.[Animesh],
Wang, O.[Oliver],
Ritschel, T.[Tobias],
Mitra, N.J.[Niloy J.],
3inGAN: Learning a 3D Generative Model from Images of a Self-similar
Scene,
3DV22(342-352)
IEEE DOI Code:
WWW Link.
2408
Training, Solid modeling, Codes, Rendering (computer graphics),
Generative adversarial networks, Cameras, 3D GAN, 3INGAN,
single 3D scene GAN
BibRef
Ruan, Y.[Yue],
Lee, H.H.[Han-Hung],
Zhang, Y.M.[Yi-Ming],
Zhang, K.[Ke],
Chang, A.X.[Angel X.],
TriCoLo: Trimodal Contrastive Loss for Text to Shape Retrieval,
WACV24(5803-5813)
IEEE DOI
2404
Representation learning, Solid modeling, Systematics, Shape,
Buildings, Algorithms, Vision + language and/or other modalities,
3D computer vision
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.H.[Zi-Hao],
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
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
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Hu, T.[Tao],
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Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Visual Sentiment Evaluation .