research-article

Reverse2Complete: Unpaired Multimodal Point Cloud Completion via Guided Diffusion

Authors:

Hossein Rahmani,

Jun LiuAuthors Info & Claims

MM '24: Proceedings of the 32nd ACM International Conference on Multimedia

Pages 5892 - 5901

https://doi.org/10.1145/3664647.3680590

Published: 28 October 2024 Publication History

Abstract

Unpaired point cloud completion involves filling in missing parts of a point cloud without requiring partial-complete correspondence. Meanwhile, since point cloud completion is an ill-posed problem, there are multiple ways to generate the missing parts. Existing unpaired completion methods usually leverage generative adversarial training by transforming partial shape encoding into a complete one in the low-dimensional latent feature space. However, "mode collapse" often occurs, where only a subset of the shapes is represented in the low-dimensional space, reducing the diversity of the generated shapes. In this paper, we propose a novel unpaired multimodal shape completion approach that directly operates on point coordinate space. We achieve unpaired completion via a single diffusion model trained on complete data by "hijacking" the generative process. We further augment the diffusion model by introducing two guidance mechanisms to facilitate mapping the partial point cloud to the complete one while preserving its original structure. We conduct extensive evaluations of our approach, which show that our method generates shapes that are more diverse and better preserve the original structures compared to alternative methods.

References

[1]

Himanshu Arora, Saurabh Mishra, Shichong Peng, Ke Li, and Ali Mahdavi-Amiri. 2022. Multimodal shape completion via implicit maximum likelihood estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2958--2967.

[2]

Yingjie Cai, Kwan-Yee Lin, Chao Zhang, Qiang Wang, Xiaogang Wang, and Hongsheng Li. 2022. Learning a structured latent space for unsupervised point cloud completion. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 5543--5553.

[3]

Rui Cao, Kaiyi Zhang, Yang Chen, Ximing Yang, and Cheng Jin. 2022. Point Cloud Completion via Multi-Scale Edge Convolution and Attention. In Proceedings of the 30th ACM International Conference on Multimedia (MM '22). Association for Computing Machinery, New York, NY, USA, 6183--6192. https://doi.org/10.1145/3503161.3548360

Digital Library

[4]

Tuo Cao, Fei Luo, Yanping Fu, Wenxiao Zhang, Shengjie Zheng, and Chunxia Xiao. 2022. DGECN: A depth-guided edge convolutional network for end-to-end 6D pose estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 3783--3792.

[5]

Tuo Cao, Wenxiao Zhang, Yanping Fu, Shengjie Zheng, Fei Luo, and Chunxia Xiao. 2023. Dgecn: A depth-guided edge convolutional network for end-to-end 6d pose estimation via attention mechanism. IEEE Transactions on Circuits and Systems for Video Technology (2023).

[6]

Zhen Cao, Wenxiao Zhang, Xin Wen, Zhen Dong, Yu-Shen Liu, Xiongwu Xiao, and Bisheng Yang. 2023. KT-Net: Knowledge Transfer for Unpaired 3D Shape Completion. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 37. 286--294.

Digital Library

[7]

Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang. 2017. Matterport3d: Learning from rgb-d data in indoor environments. arXiv preprint arXiv:1709.06158 (2017).

[8]

Junxian Chen, Ying Liu, Yiqi Liang, Dandan Long, Xiaolin He, and Ruihui Li. 2023. SD-Net: Spatially-Disentangled Point Cloud Completion Network. In Proceedings of the 30th ACM International Conference on Multimedia (MM '23). Association for Computing Machinery, 1283--1293. https://doi.org/10.1145/3581783.3611716

Digital Library

[9]

Xuelin Chen, Baoquan Chen, and Niloy J Mitra. 2019. Unpaired point cloud completion on real scans using adversarial training. arXiv preprint arXiv:1904.00069 (2019).

[10]

Ruihang Chu, Enze Xie, Shentong Mo, Zhenguo Li, Matthias Nießner, Chi-Wing Fu, and Jiaya Jia. 2024. Diffcomplete: Diffusion-based generative 3d shape completion. Advances in Neural Information Processing Systems 36 (2024).

[11]

Ruikai Cui, Shi Qiu, Saeed Anwar, Jiawei Liu, Chaoyue Xing, Jing Zhang, and Nick Barnes. 2023. P2c: Self-supervised point cloud completion from single partial clouds. In Proceedings of the IEEE/CVF International Conference on Computer Vision. 14351?14360.

[12]

Ruikai Cui, Shi Qiu, Saeed Anwar, Jing Zhang, and Nick Barnes. 2022. Energy- Based Residual Latent Transport for Unsupervised Point Cloud Completion. arXiv preprint arXiv:2211.06820 (2022).

[13]

Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner. 2017. Scannet: Richly-annotated 3d reconstructions of indoor scenes. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 5828--5839.

[14]

Angela Dai, Charles Ruizhongtai Qi, and Matthias Nießner. 2017. Shape completion using 3d-encoder-predictor cnns and shape synthesis. In CVPR. 5868--5877.

[15]

Donglin Di, Jiahui Yang, Chaofan Luo, Zhou Xue, Wei Chen, Xun Yang, and Yue Gao. 2024. Hyper-3DG: Text-to-3D Gaussian Generation via Hypergraph. arXiv preprint arXiv:2403.09236 (2024).

[16]

Jin Gao, Jialing Zhang, Xihui Liu, Trevor Darrell, Evan Shelhamer, and Dequan Wang. 2022. Back to the source: Diffusion-driven test-time adaptation. arXiv preprint arXiv:2207.03442 (2022).

[17]

Andreas Geiger, Philip Lenz, and Raquel Urtasun. 2012. Are we ready for autonomous driving? the kitti vision benchmark suite. In 2012 IEEE conference on computer vision and pattern recognition. IEEE, 3354--3361.

Digital Library

[18]

Dan Guo, Kun Li, Bin Hu, Yan Zhang, and Meng Wang. 2024. Benchmarking Micro-action Recognition: Dataset, Methods, and Applications. IEEE Transactions on Circuits and Systems for Video Technology, Vol. 34, 7 (2024), 6238--6252. https://doi.org/10.1109/TCSVT.2024.3358415

Digital Library

[19]

Xiaoguang Han, Zhen Li, Haibin Huang, Evangelos Kalogerakis, and Yizhou Yu. 2017. High-resolution shape completion using deep neural networks for global structure and local geometry inference. In ICCV. 85--93.

[20]

Zhizhong Han, Xiyang Wang, Yu-Shen Liu, and Matthias Zwicker. 2019. Multi-angle point cloud-vae: Unsupervised feature learning for 3d point clouds from multiple angles by joint self-reconstruction and half-to-half prediction. In 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 10441--10450.

[21]

Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising diffusion probabilistic models. Advances in Neural Information Processing Systems, Vol. 33 (2020), 6840--6851.

[22]

Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising diffusion probabilistic models. Advances in Neural Information Processing Systems, Vol. 33 (2020), 6840--6851.

[23]

Tianxin Huang, Hao Zou, Jinhao Cui, Xuemeng Yang, Mengmeng Wang, Xiangrui Zhao, Jiangning Zhang, Yi Yuan, Yifan Xu, and Yong Liu. 2021. RFNet: Recurrent Forward Network for Dense Point Cloud Completion. In Proceedings of the IEEE/CVF International Conference on Computer Vision. 12508--12517.

[24]

Zitian Huang, Yikuan Yu, Jiawen Xu, Feng Ni, and Xinyi Le. 2020. PF-Net: Point fractal network for 3D point cloud completion. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 7662--7670.

[25]

Michael Kazhdan and Hugues Hoppe. 2013. Screened poisson surface reconstruction. ToG, Vol. 32, 3 (2013), 29.

Digital Library

[26]

Young Min Kim, Niloy J Mitra, Dong-Ming Yan, and Leonidas Guibas. 2012. Acquiring 3D indoor environments with variability and repetition. TOG, Vol. 31, 6 (2012), 138.

Digital Library

[27]

Dongping Li, Tianjia Shao, Hongzhi Wu, and Kun Zhou. 2016. Shape completion from a single rgbd image. TVCG, Vol. 23, 7 (2016), 1809--1822.

[28]

Yangyan Li, Angela Dai, Leonidas Guibas, and Matthias Nießner. 2015. Database-assisted object retrieval for real-time 3d reconstruction. In CGF, Vol. 34. Wiley Online Library, 435--446.

Digital Library

[29]

Yicong Li, Xun Yang, An Zhang, Chun Feng, Xiang Wang, and Tat-Seng Chua. 2023. Redundancy-aware transformer for video question answering. In Proceedings of the 31st ACM International Conference on Multimedia. 3172--3180.

Digital Library

[30]

Liu Liu, Jianming Du, Hao Wu, Xun Yang, Zhenguang Liu, Richang Hong, and Meng Wang. 2023. Category-level articulated object 9d pose estimation via reinforcement learning. In Proceedings of the 31st ACM International Conference on Multimedia. 728--736.

Digital Library

[31]

Minghua Liu, Lu Sheng, Sheng Yang, Jing Shao, and Shi-Min Hu. 2020. Morphing and sampling network for dense point cloud completion. In Proceedings of the AAAI conference on artificial intelligence, Vol. 34. 11596--11603.

[32]

Zhijian Liu, Haotian Tang, Yujun Lin, and Song Han. 2019. Point-Voxel CNN for Efficient 3D Deep Learning. In Conference on Neural Information Processing Systems (NeurIPS).

[33]

Chen Long, Wenxiao Zhang, Zhe Chen, Haiping Wang, Yuan Liu, Peiling Tong, Zhen Cao, Zhen Dong, and Bisheng Yang. 2024. SparseDC: Depth Completion from sparse and non-uniform inputs. Information Fusion, Vol. 110 (2024), 102470.

[34]

Chen Long, WenXiao Zhang, Ruihui Li, Hao Wang, Zhen Dong, and Bisheng Yang. 2022. Pc2-pu: Patch correlation and point correlation for effective point cloud upsampling. In Proceedings of the 30th ACM International Conference on Multimedia. 2191--2201.

Digital Library

[35]

Chaofan Luo, Donglin Di, Yongjia Ma, Zhou Xue, Chen Wei, Xun Yang, and Yebin Liu. 2024. TrAME: Trajectory-Anchored Multi-View Editing for Text-Guided 3D Gaussian Splatting Manipulation. arXiv preprint arXiv:2407.02034 (2024).

[36]

Shitong Luo and Wei Hu. 2021. Diffusion probabilistic models for 3d point cloud generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2837--2845.

[37]

Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, and Dahua Lin. 2021. A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion. ArXiv, Vol. abs/2112.03530 (2021).

[38]

Changfeng Ma, Yang Yang, Jie Guo, Mingqiang Wei, Chongjun Wang, Yanwen Guo, and Wenping Wang. 2023. Collaborative completion and segmentation for partial point clouds with outliers. IEEE Transactions on Visualization and Computer Graphics (2023).

[39]

Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon. 2021. Sdedit: Guided image synthesis and editing with stochastic differential equations. In International Conference on Learning Representations.

[40]

Niloy J Mitra, Leonidas J Guibas, and Mark Pauly. 2006. Partial and approximate symmetry detection for 3D geometry. In TOG, Vol. 25. ACM, 560--568.

Digital Library

[41]

Andrew Nealen, Takeo Igarashi, Olga Sorkine, and Marc Alexa. 2006. Laplacian mesh optimization. In Proceedings of the 4th international conference on Computer graphics and interactive techniques in Australasia and Southeast Asia. ACM, 381--389.

Digital Library

[42]

Yinyu Nie, Yiqun Lin, Xiaoguang Han, Shihui Guo, Jian Chang, Shuguang Cui, Jian Zhang, et al. 2020. Skeleton-bridged point completion: From global inference to local adjustment. Advances in Neural Information Processing Systems, Vol. 33 (2020), 16119--16130.

[43]

Liang Pan, Xinyi Chen, Zhongang Cai, Junzhe Zhang, Haiyu Zhao, Shuai Yi, and Ziwei Liu. 2021. Variational Relational Point Completion Network. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 8524--8533.

[44]

Mark Pauly, Niloy J Mitra, Johannes Wallner, Helmut Pottmann, and Leonidas J Guibas. 2008. Discovering structural regularity in 3D geometry. In TOG, Vol. 27. ACM, 43.

Digital Library

[45]

Audrey Richard, Ian Cherabier, Martin R Oswald, Marc Pollefeys, and Konrad Schindler. 2020. Kaplan: A 3d point descriptor for shape completion. (2020), 101--110.

[46]

Muhammad Sarmad, Hyunjoo Jenny Lee, and Young Min Kim. 2019. RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion. In CVPR. 5898--5907.

[47]

Yifei Shi, Pinxin Long, Kai Xu, Hui Huang, and Yueshan Xiong. 2016. Data-driven contextual modeling for 3d scene understanding. Computers & Graphics, Vol. 55 (2016), 55--67.

Digital Library

[48]

Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli. 2015. Deep unsupervised learning using nonequilibrium thermodynamics. In International Conference on Machine Learning. PMLR, 2256--2265.

[49]

Jiaming Song, Chenlin Meng, and Stefano Ermon. 2020. Denoising diffusion implicit models. arXiv preprint arXiv:2010.02502 (2020).

[50]

Olga Sorkine and Daniel Cohen-Or. 2004. Least-squares meshes. In Proceedings Shape Modeling Applications,. IEEE, 191--199.

[51]

Junshu Tang, Zhijun Gong, Ran Yi, Yuan Xie, and Lizhuang Ma. 2022. LAKe-Net: topology-aware point cloud completion by localizing aligned keypoints. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 1726--1735.

[52]

Lyne P Tchapmi, Vineet Kosaraju, Hamid Rezatofighi, Ian Reid, and Silvio Savarese. 2019. TopNet: Structural Point Cloud Decoder. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 383--392.

[53]

Sebastian Thrun and Ben Wegbreit. 2005. Shape from symmetry. In ICCV, Vol. 2. IEEE, 1824--1831.

Digital Library

[54]

Xiaogang Wang, Marcelo H Ang, and Gim Hee Lee. 2021. Voxel-based Network for Shape Completion by Leveraging Edge Generation. In Proceedings of the IEEE/CVF International Conference on Computer Vision. 13189--13198.

[55]

Xiaogang Wang, Marcelo H Ang Jr, and Gim Hee Lee. 2020. Cascaded refinement network for point cloud completion. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 790--799.

[56]

Yida Wang, David Joseph Tan, Nassir Navab, and Federico Tombari. 2020. Softpoolnet: Shape descriptor for point cloud completion and classification. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part III 16. Springer, 70--85.

[57]

Ziqi Wang, Fei Luo, Xiaoxiao Long, Wenxiao Zhang, and Chunxia Xiao. 2023. Learning long-range information with dual-scale transformers for indoor scene completion. In 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 18523--18533.

[58]

Xin Wen, Zhizhong Han, Yan-Pei Cao, Pengfei Wan, Wen Zheng, and Yu-Shen Liu. 2021. Cycle4completion: Unpaired point cloud completion using cycle transformation with missing region coding. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 13080--13089.

[59]

Xin Wen, Tianyang Li, Zhizhong Han, and Yu-Shen Liu. 2020. Point cloud completion by skip-attention network with hierarchical folding. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 1939--1948.

[60]

Rundi Wu, Xuelin Chen, Yixin Zhuang, and Baoquan Chen. 2020. Multimodal Shape Completion via Conditional Generative Adversarial Networks. In The European Conference on Computer Vision (ECCV).

Digital Library

[61]

Xianzu Wu, Xianfeng Wu, Tianyu Luan, Yajing Bai, Zhongyuan Lai, and Junsong Yuan. 2024. FSC: Few-point Shape Completion. arXiv preprint arXiv:2403.07359 (2024).

[62]

Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao. 2015. 3d shapenets: A deep representation for volumetric shapes. In CVPR. 1912--1920.

[63]

Yaqi Xia, Yan Xia, Wei Li, Rui Song, Kailang Cao, and Uwe Stilla. 2021. Asfm-net: Asymmetrical siamese feature matching network for point completion. (2021), 1938--1947.

[64]

Yaqi Xia, Yan Xia, Wei Li, Rui Song, Kailang Cao, and Uwe Stilla. 2021. ASFM-Net: Asymmetrical Siamese Feature Matching Network for Point Completion. In Proceedings of the 29th ACM International Conference on Multimedia (MM '21). Association for Computing Machinery, 1938--1947. https://doi.org/10.1145/3474085.3475348

Digital Library

[65]

Peng Xiang, Xin Wen, Yu-Shen Liu, Yan-Pei Cao, Pengfei Wan, Wen Zheng, and Zhizhong Han. 2021. Snowflakenet: Point cloud completion by snowflake point deconvolution with skip-transformer. In Proceedings of the IEEE/CVF International Conference on Computer Vision. 5499--5509.

[66]

Haozhe Xie, Hongxun Yao, Shangchen Zhou, Jiageng Mao, Shengping Zhang, and Wenxiu Sun. 2020. GRNet: gridding residual network for dense point cloud completion. In European Conference on Computer Vision. Springer, 365--381.

Digital Library

[67]

Hang Xu, Chen Long, Wenxiao Zhang, Yuan Liu, Zhen Cao, Zhen Dong, and Bisheng Yang. 2024. Explicitly Guided Information Interaction Network for Cross-modal Point Cloud Completion. arXiv preprint arXiv:2407.02887 (2024).

[68]

Xingguang Yan, Liqiang Lin, Niloy J Mitra, Dani Lischinski, Daniel Cohen-Or, and Hui Huang. 2022. Shapeformer: Transformer-based shape completion via sparse representation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 6239--6249.

[69]

Xuejun Yan, Hongyu Yan, Jingjing Wang, Hang Du, Zhihong Wu, Di Xie, Shiliang Pu, and Li Lu. 2022. Fbnet: Feedback network for point cloud completion. In European Conference on Computer Vision. Springer, 676--693.

Digital Library

[70]

Bo Yang, Hongkai Wen, Sen Wang, Ronald Clark, Andrew Markham, and Niki Trigoni. 2017. 3d object reconstruction from a single depth view with adversarial learning. In ICCV. 679--688.

[71]

Xun Yang, Tianyu Chang, Tianzhu Zhang, Shanshan Wang, Richang Hong, and Meng Wang. 2024. Learning Hierarchical Visual Transformation for Domain Generalizable Visual Matching and Recognition. International Journal of Computer Vision (2024), 1--27.

Digital Library

[72]

Xun Yang, Fuli Feng, Wei Ji, Meng Wang, and Tat-Seng Chua. 2021. Deconfounded video moment retrieval with causal intervention. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. 1--10.

Digital Library

[73]

Xun Yang, Shanshan Wang, Jian Dong, Jianfeng Dong, Meng Wang, and Tat-Seng Chua. 2022. Video moment retrieval with cross-modal neural architecture search. IEEE Transactions on Image Processing, Vol. 31 (2022), 1204--1216.

[74]

Xun Yang, Jianming Zeng, Dan Guo, Shanshan Wang, Jianfeng Dong, and Meng Wang. 2024. Robust Video Question Answering via Contrastive Cross-Modality Representation Learning. SCIENCE CHINA Information Sciences (2024).

[75]

Xumin Yu, Yongming Rao, Ziyi Wang, Zuyan Liu, Jiwen Lu, and Jie Zhou. 2021. Pointr: Diverse point cloud completion with geometry-aware transformers. In Proceedings of the IEEE/CVF International Conference on Computer Vision. 12498--12507.

[76]

Wentao Yuan, Tejas Khot, David Held, Christoph Mertz, and Martial Hebert. 2018. Pcn: Point completion network. In 3DV. IEEE, 728--737.

[77]

Junzhe Zhang, Xinyi Chen, Zhongang Cai, Liang Pan, Haiyu Zhao, Shuai Yi, Chai Kiat Yeo, Bo Dai, and Chen Change Loy. 2021. Unsupervised 3d shape completion through gan inversion. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 1768--1777.

[78]

Wenxiao Zhang, Zhen Dong, Jun Liu, Qingan Yan, Chunxia Xiao, et al. 2022. Point cloud completion via skeleton-detail transformer. IEEE Transactions on Visualization and Computer Graphics (2022).

[79]

Wenxiao Zhang, Chengjiang Long, Qingan Yan, Alix LH Chow, and Chunxia Xiao. 2020. Multi-stage point completion network with critical set supervision. Computer Aided Geometric Design, Vol. 82 (2020), 101925.

[80]

Wenxiao Zhang, Ziqi Wang, Li Xu, Xun Yang, and Jun Liu. [n.,d.]. Informative Point cloud Dataset Extraction for Classification via Gradient-based Points Moving. In ACM Multimedia 2024.

Digital Library

[81]

Wenxiao Zhang and Chunxia Xiao. 2019. PCAN: 3D attention map learning using contextual information for point cloud based retrieval. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 12436--12445.

[82]

Wenxiao Zhang, Qingan Yan, and Chunxia Xiao. 2020. Detail preserved point cloud completion via separated feature aggregation. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXV 16. Springer, 512--528.

Digital Library

[83]

Wenxiao Zhang, Huajian Zhou, Zhen Dong, Qingan Yan, and Chunxia Xiao. 2022. Rank-PointRetrieval: Reranking Point Cloud Retrieval via a Visually Consistent Registration Evaluation. IEEE Transactions on Visualization and Computer Graphics (2022).

[84]

Xuancheng Zhang, Yutong Feng, Siqi Li, Changqing Zou, Hai Wan, Xibin Zhao, Yandong Guo, and Yue Gao. 2021. View-guided point cloud completion. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 15890--15899.

[85]

Min Zhao, Fan Bao, Chongxuan Li, and Jun Zhu. 2022. Egsde: Unpaired image-to-image translation via energy-guided stochastic differential equations. arXiv preprint arXiv:2207.06635 (2022).

[86]

Xi Zhao, Bowen Zhang, Jinji Wu, Ruizhen Hu, and Taku Komura. 2021. Relationship-based point cloud completion. IEEE transactions on visualization and computer graphics, Vol. 28, 12 (2021), 4940--4950.

Digital Library

[87]

Haoran Zhou, Yun Cao, Wenqing Chu, Junwei Zhu, Tong Lu, Ying Tai, and Chengjie Wang. 2022. Seedformer: Patch seeds based point cloud completion with upsample transformer. In Computer Vision-ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part III. Springer, 416--432.

[88]

Linqi Zhou, Yilun Du, and Jiajun Wu. 2021. 3d shape generation and completion through point-voxel diffusion. In Proceedings of the IEEE/CVF International Conference on Computer Vision. 5826--5835.

[89]

Zhe Zhu, Honghua Chen, Xing He, Weiming Wang, Jing Qin, and Mingqiang Wei. 2023. SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV).

[90]

Zhe Zhu, Liangliang Nan, Haoran Xie, Honghua Chen, Jun Wang, Mingqiang Wei, and Jing Qin. 2023. Csdn: Cross-modal shape-transfer dual-refinement network for point cloud completion. IEEE Transactions on Visualization and Computer Graphics (2023).

Cited By

Zhang WWang ZXu LYang XLiu JCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Informative Point cloud Dataset Extraction for Classification via Gradient-based Points MovingProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3680767(6384-6393)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3680767

Index Terms

Reverse2Complete: Unpaired Multimodal Point Cloud Completion via Guided Diffusion
1. Computing methodologies
  1. Computer graphics
    1. Shape modeling
      1. Point-based models

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cover image ACM Conferences

MM '24: Proceedings of the 32nd ACM International Conference on Multimedia

October 2024

11719 pages

ISBN:9798400706868

DOI:10.1145/3664647

General Chairs:
Jianfei Cai
Monash University, Australia
,
Mohan Kankanhalli
NUS, Singapore
,
Balakrishnan Prabhakaran
UT Dallas, USA
,
Susanne Boll
University of Oldenburg, Germany
,
Program Chairs:
Ramanathan Subramanian
University of Canberra & IIT Ropar, Australia
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Liang Zheng
Australian National University, Australia
,
Vivek K. Singh
Rutgers University, USA
,
Pablo Cesar
Centrum Wiskunde & Informatica, Netherlands
,
Lexing Xie
Australian National University, Australia
,
Dong Xu
University of Hong Kong, Hong Kong

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Cited By

Zhang WWang ZXu LYang XLiu JCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Informative Point cloud Dataset Extraction for Classification via Gradient-based Points MovingProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3680767(6384-6393)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3680767

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