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Pre-training by numerous image data has become de-facto for robust 2D representations.
Illumination for computer generated pictures
Bui Tuong Phong · 1975
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Shapenet: An information-rich 3d model repository
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Yfcc100m: The new data in multimedia research
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue, Bill Freeman, and Josh Tenenbaum · 2016
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A scalable active framework for region annotation in 3d shape collections
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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
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A point set generation network for 3d object reconstruction from a single image
Haoqiang Fan, Hao Su, and Leonidas J Guibas · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles R Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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So-net: Self-organizing network for point cloud analysis
Jiaxin Li, Ben M Chen, and Gim Hee Lee · 2018
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Pointcnn: Convolution on x-transformed points
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018
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A deeper look at 3d shape classifiers
Jong-Chyi Su, Matheus Gadelha, Rui Wang, and Subhransu Maji · 2018
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Spidercnn: Deep learning on point sets with parameterized convolutional filters
Yifan Xu, Tianqi Fan, Mingye Xu, Long Zeng, and Yu Qiao · 2018
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Foldingnet: Point cloud auto-encoder via deep grid deformation
Yaoqing Yang, Chen Feng, Yiru Shen, and Dong Tian · 2018
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View inter-prediction gan: Unsupervised representation learning for 3d shapes by learning global shape memories to support local view predictions
Zhizhong Han, Mingyang Shang, Yu-Shen Liu, and Matthias Zwicker · 2019
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Pu-gan: a point cloud upsampling adversarial network
Ruihui Li, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, and Pheng-Ann Heng · 2019
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Relation-shape convolutional neural network for point cloud analysis
Yongcheng Liu, Bin Fan, Shiming Xiang, and Chunhong Pan · 2019
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Self-supervised deep learning on point clouds by reconstructing space
Jonathan Sauder and Bjarne Sievers · 2019
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Self-supervised deep learning on point clouds by reconstructing space
Jonathan Sauder and Bjarne Sievers · 2019
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Fcos: Fully convolutional one-stage object detection
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2019
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Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data
Mikaela Angelina Uy, Quang-Hieu Pham, Binh-Son Hua, Thanh Nguyen, and Sai-Kit Yeung · 2019
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Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E Sarma, Michael M Bronstein, and Justin M Solomon · 2019
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Hyperspectral classification based on lightweight 3-d-cnn with transfer learning
Haokui Zhang, Ying Li, Yenan Jiang, Peng Wang, Qiang Shen, and Chunhua Shen · 2019
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Image2point: 3d point-cloud understanding with pretrained 2d convnets
Chenfeng Xu, Shijia Yang, Bohan Zhai, Bichen Wu, Xiangyu Yue, Wei Zhan, Peter Vajda, Kurt Keutzer, and Masayoshi Tomizuka · 2021
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Paconv: Position adaptive convolution with dynamic kernel assembling on point clouds
Mutian Xu, Runyu Ding, Hengshuang Zhao, and Xiaojuan Qi · 2021
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Point-bert: Pre-training 3d point cloud transformers with masked point modeling
Xumin Yu, Lulu Tang, Yongming Rao, Tiejun Huang, Jie Zhou, and Jiwen Lu · 2021
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Pointclip: Point cloud understanding by clip
Renrui Zhang, Ziyu Guo, Wei Zhang, Kunchang Li, Xupeng Miao, Bin Cui, Yu Qiao, Peng Gao, and Hongsheng Li · 2021
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Self-supervised pretraining of 3d features on any point-cloud
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Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Bootstrap your own latent-a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, et al · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Self-supervised learning of point clouds via orientation estimation
Omid Poursaeed, Tianxing Jiang, Han Qiao, Nayun Xu, and Vladimir G Kim · 2020
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Global-local bidirectional reasoning for unsupervised representation learning of 3d point clouds
Yongming Rao, Jiwen Lu, and Jie Zhou · 2020
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Learning localized representations of point clouds with graph-convolutional generative adversarial networks
Diego Valsesia, Giulia Fracastoro, and Enrico Magli · 2020
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Pointcontrast: Unsupervised pre-training for 3d point cloud understanding
Saining Xie, Jiatao Gu, Demi Guo, Charles R Qi, Leonidas Guibas, and Or Litany · 2020
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Zaiwei Zhang, Rohit Girdhar, Armand Joulin, and Ishan Misra · 2021
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Point transformer
Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip HS Torr, and Vladlen Koltun · 2021
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ibot: Image bert pre-training with online tokenizer
Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, and Tao Kong · 2021
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Crosspoint: Self-supervised cross-modal contrastive learning for 3d point cloud understanding
Mohamed Afham, Isuru Dissanayake, Dinithi Dissanayake, Amaya Dharmasiri, Kanchana Thilakarathna, and Ranga Rodrigo · 2022
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Rethinking network design and local geometry in point cloud: A simple residual MLP framework
Anonymous · 2022
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Data2vec: A general framework for self-supervised learning in speech, vision and language
Alexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu, and Michael Auli · 2022
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Pos-bert: Point cloud one-stage bert pre-training
Kexue Fu, Peng Gao, ShaoLei Liu, Renrui Zhang, Yu Qiao, and Manning Wang · 2022
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Distillation with contrast is all you need for self-supervised point cloud representation learning
Kexue Fu, Peng Gao, Renrui Zhang, Hongsheng Li, Yu Qiao, and Manning Wang · 2022
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Convmae: Masked convolution meets masked autoencoders
Peng Gao, Teli Ma, Hongsheng Li, Jifeng Dai, and Yu Qiao · 2022
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Calip: Zero-shot enhancement of clip with parameter-free attention
Ziyu Guo, Renrui Zhang, Longtian Qiu, Xianzheng Ma, Xupeng Miao, Xuming He, and Bin Cui · 2022
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Milan: Masked image pretraining on language assisted representation
Zejiang Hou, Fei Sun, Yen-Kuang Chen, Yuan Xie, and Sun-Yuan Kung · 2022
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Green hierarchical vision transformer for masked image modeling
Lang Huang, Shan You, Mingkai Zheng, Fei Wang, Chen Qian, and Toshihiko Yamasaki · 2022
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Masked autoencoders in 3d point cloud representation learning
Jincen Jiang, Xuequan Lu, Lizhi Zhao, Richard Dazeley, and Meili Wang · 2022
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Simipu: Simple 2d image and 3d point cloud unsupervised pre-training for spatial-aware visual representations
Zhenyu Li, Zehui Chen, Ang Li, Liangji Fang, Qinhong Jiang, Xianming Liu, Junjun Jiang, Bolei Zhou, and Hang Zhao · 2022
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Masked discrimination for self-supervised learning on point clouds
Haotian Liu, Mu Cai, and Yong Jae Lee · 2022
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Mixmim: Mixed and masked image modeling for efficient visual representation learning
Jihao Liu, Xin Huang, Yu Liu, and Hongsheng Li · 2022
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Masked autoencoders for point cloud self-supervised learning
Yatian Pang, Wenxiao Wang, Francis EH Tay, Wei Liu, Yonghong Tian, and Li Yuan · 2022
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Pix4point: Image pretrained transformers for 3d point cloud understanding
Guocheng Qian, Xingdi Zhang, Abdullah Hamdi, and Bernard Ghanem · 2022
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Image-to-lidar self-supervised distillation for autonomous driving data
Corentin Sautier, Gilles Puy, Spyros Gidaris, Alexandre Boulch, Andrei Bursuc, and Renaud Marlet · 2022
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P2p: Tuning pre-trained image models for point cloud analysis with point-to-pixel prompting
Ziyi Wang, Xumin Yu, Yongming Rao, Jie Zhou, and Jiwen Lu · 2022
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2dpass: 2d priors assisted semantic segmentation on lidar point clouds
Xu Yan, Jiantao Gao, Chaoda Zheng, Chao Zheng, Ruimao Zhang, Shuguang Cui, and Zhen Li · 2022
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Point-m2ae: Multi-scale masked autoencoders for hierarchical point cloud pre-training
Renrui Zhang, Ziyu Guo, Peng Gao, Rongyao Fang, Bin Zhao, Dong Wang, Yu Qiao, and Hongsheng Li · 2022
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Pointclip v2: Adapting clip for powerful 3d open-world learning
Xiangyang Zhu, Renrui Zhang, Bowei He, Ziyao Zeng, Shanghang Zhang, and Peng Gao · 2022
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