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Towards holistic understanding of 3D scenes, a general 3D segmentation method is needed that can segment diverse objects without restrictions on object quantity or categories, while also reflecting the inherent hierarchical structure.
Structurenet: Hierarchical graph networks for 3d shape generation
Kaichun Mo, Paul Guerrero, Li Yi, Hao Su, Peter Wonka, Niloy Mitra, and Leonidas J Guibas · 1908
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Image segmentation by clustering
Guy Barrett Coleman and Harry C Andrews · 1979
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Interactive 3d segmentation of mri and ct volumes using morphological operations
Karl Heinz Höhne and William A Hanson · 1992
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Efficient graph-based image segmentation
Pedro F Felzenszwalb and Daniel P Huttenlocher · 2004
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3d segmentation of unstructured point clouds for building modelling
Peter Dorninger and Clemens Nothegger · 2007
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Efficient ransac for point-cloud shape detection
Ruwen Schnabel, Roland Wahl, and Reinhard Klein · 2007
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Slic superpixels compared to state-of-the-art superpixel methods
Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Süsstrunk · 2012
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Point cloud labeling using 3d convolutional neural network
Jing Huang and Suya You · 2016
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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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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Pyramid scene parsing network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
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Depth-aware cnn for rgb-d segmentation
Weiyue Wang and Ulrich Neumann · 2018
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Panoptic segmentation
Alexander Kirillov, Kaiming He, Ross Girshick, Carsten Rother, and Piotr Dollár · 2019
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Point-voxel cnn for efficient 3d deep learning
Zhijian Liu, Haotian Tang, Yujun Lin, and Song Han · 2019
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The Replica dataset: A digital replica of indoor spaces
Julian Straub, Thomas Whelan, Lingni Ma, Yufan Chen, Erik Wijmans, Simon Green, Jakob J. Engel, Raul Mur-Artal, Carl Ren, Shobhit Verma, Anton Clarkson, Mingfei Yan, Brian Budge, Yajie Yan, Xiaqing Pan, June Yon, Yuyang Zou, Kimberly Leon, Nigel Carter, Jesus Briales, Tyler Gillingham, Elias Mueggler, Luis Pesqueira, Manolis Savva, Dhruv Batra, Hauke M. Strasdat, Renzo De Nardi, Michael Goesele, Steven Lovegrove, and Richard Newcombe · 2019
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Learning object bounding boxes for 3d instance segmentation on point clouds
Bo Yang, Jianan Wang, Ronald Clark, Qingyong Hu, Sen Wang, Andrew Markham, and Niki Trigoni · 2019
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Gspn: Generative shape proposal network for 3d instance segmentation in point cloud
Li Yi, Wang Zhao, He Wang, Minhyuk Sung, and Leonidas J Guibas · 2019
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Bsp-net: Generating compact meshes via binary space partitioning
Zhiqin Chen, Andrea Tagliasacchi, and Hao Zhang · 2020
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Occuseg: Occupancy-aware 3d instance segmentation
Lei Han, Tian Zheng, Lan Xu, and Lu Fang · 2020
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Randla-net: Efficient semantic segmentation of large-scale point clouds
Qingyong Hu, Bo Yang, Linhai Xie, Stefano Rosa, Yulan Guo, Zhihua Wang, Niki Trigoni, and Andrew Markham · 2020
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Prototypical contrastive learning of unsupervised representations
Junnan Li, Pan Zhou, Caiming Xiong, and Steven Hoi · 2020
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Malleable 2.5 d convolution: Learning receptive fields along the depth-axis for rgb-d scene parsing
Ins-conv: Incremental sparse convolution for online 3d segmentation
Leyao Liu, Tian Zheng, Yun-Jou Lin, Kai Ni, and Lu Fang · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
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Neural volumetric object selection
Zhongzheng Ren, Aseem Agarwala, Bryan Russell, Alexander G Schwing, and Oliver Wang · 2022
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Reviving iterative training with mask guidance for interactive segmentation
Konstantin Sofiiuk, Ilya A Petrov, and Anton Konushin · 2022
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Object-compositional neural implicit surfaces
Qianyi Wu, Xian Liu, Yuedong Chen, Kejie Li, Chuanxia Zheng, Jianfei Cai, and Jianmin Zheng · 2022
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Capri-net: Learning compact cad shapes with adaptive primitive assembly
Fenggen Yu, Zhiqin Chen, Manyi Li, Aditya Sanghi, Hooman Shayani, Ali Mahdavi-Amiri, and Hao Zhang · 2022
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Yajie Xing, Jingbo Wang, and Gang Zeng · 2020
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Per-pixel classification is not all you need for semantic segmentation
Bowen Cheng, Alex Schwing, and Alexander Kirillov · 2021
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip HS Torr, et al · 2021
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In-place scene labelling and understanding with implicit scene representation
Shuaifeng Zhi, Tristan Laidlow, Stefan Leutenegger, and Andrew J Davison · 2021
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Use all the labels: A hierarchical multi-label contrastive learning framework
Shu Zhang, Ran Xu, Caiming Xiong, and Chetan Ramaiah · 2022
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Contrastive lift: 3d object instance segmentation by slow-fast contrastive fusion
Yash Bhalgat, Iro Laina, João F Henriques, Andrew Zisserman, and Andrea Vedaldi · 2023
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Segment anything in 3d with nerfs
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Openscene: 3d scene understanding with open vocabularies
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Panoptic lifting for 3d scene understanding with neural fields
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Openmask3d: Open-vocabulary 3d instance segmentation
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