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Instance segmentation in 3D is a challenging task due to the lack of large-scale annotated datasets.
A density-based algorithm for discovering clusters in large spatial databases with noise
Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu, et al · 1996
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Mean shift: A robust approach toward feature space analysis
Dorin Comaniciu and Peter Meer · 2002
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Learning a similarity metric discriminatively, with application to face verification
Sumit Chopra, Raia Hadsell, and Yann LeCun · 2005
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The elements of statistical learning: data mining, inference, and prediction
Trevor Hastie, Robert Tibshirani, Jerome H Friedman, and Jerome H Friedman · 2009
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Dense 3d semantic mapping of indoor scenes from rgb-d images
Alexander Hermans, Georgios Floros, and Bastian Leibe · 2014
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Joint semantic segmentation and 3d reconstruction from monocular video
Abhijit Kundu, Yin Li, Frank Dellaert, Fuxin Li, and James M Rehg · 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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Incremental dense semantic stereo fusion for large-scale semantic scene reconstruction
Vibhav Vineet, Ondrej Miksik, Morten Lidegaard, Matthias Nießner, Stuart Golodetz, Victor A Prisacariu, Olaf Kähler, David W Murray, Shahram Izadi, Patrick Pérez, et al · 2015
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Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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Semantic instance segmentation with a discriminative loss function
Bert De Brabandere, Davy Neven, and Luc Van Gool · 2017
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Semantic instance segmentation via deep metric learning
Alireza Fathi, Zbigniew Wojna, Vivek Rathod, Peng Wang, Hyun Oh Song, Sergio Guadarrama, and Kevin P Murphy · 2017
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Multi-view deep learning for consistent semantic mapping with RGB-D cameras
Lingni Ma, Jörg Stückler, Christian Kerl, and Daniel Cremers · 2017
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Semanticfusion: Dense 3d semantic mapping with convolutional neural networks
John McCormac, Ankur Handa, Andrew Davison, and Stefan Leutenegger · 2017
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hdbscan: Hierarchical density based clustering
Leland McInnes, John Healy, and Steve Astels · 2017
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Associative embedding: End-to-end learning for joint detection and grouping
Alejandro Newell, Zhiao Huang, and Jia Deng · 2017
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Meaningful maps with object-oriented semantic mapping
Niko Sünderhauf, Trung T Pham, Yasir Latif, Michael Milford, and Ian Reid · 2017
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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola · 2017
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Cnn-slam: Real-time dense monocular slam with learned depth prediction
Keisuke Tateno, Federico Tombari, Iro Laina, and Nassir Navab · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Blender - a 3D modelling and rendering package
Blender Online Community · 2018
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Recurrent pixel embedding for instance grouping
Shu Kong and Charless C Fowlkes · 2018
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Semi-convolutional operators for instance segmentation
David Novotny, Samuel Albanie, Diane Larlus, and Andrea Vedaldi · 2018
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Lvis: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollar, and Ross Girshick · 2019
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross B. Girshick · 2019
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Panoptic segmentation
Alexander Kirillov, Kaiming He, Ross B. Girshick, Carsten Rother, and Piotr Dollár · 2019
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Panopticfusion: Online volumetric semantic mapping at the level of stuff and things
Gaku Narita, Takashi Seno, Tomoya Ishikawa, and Yohsuke Kaji · 2019
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Scene representation networks: Continuous 3D-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 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, et al · 2019
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Representation learning with contrastive predictive coding
Aäron van den Oord, Yazhe Li, and Oriol Vinyals · 2019
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Masked-attention mask transformer for universal image segmentation
Bowen Cheng, Ishan Misra, Alexander G Schwing, Alexander Kirillov, and Rohit Girdhar · 2022
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Google scanned objects: A high-quality dataset of 3d scanned household items
Laura Downs, Anthony Francis, Nate Koenig, Brandon Kinman, Ryan Hickman, Krista Reymann, Thomas B McHugh, and Vincent Vanhoucke · 2022
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Panoptic NeRF: 3d-to-2d label transfer for panoptic urban scene segmentation
Xiao Fu, Shangzhan Zhang, Tianrun Chen, Yichong Lu, Lanyun Zhu, Xiaowei Zhou, Andreas Geiger, and Yiyi Liao · 2022
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Kubric: a scalable dataset generator
Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam Laradji, Hsueh-Ti (Derek) Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, Cengiz Oztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, and Andrea Tagliasacchi · 2022
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Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton · 2020
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Neural sparse voxel fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020
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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 · 2020
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On mutual information maximization for representation learning
Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, and Mario Lucic · 2020
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Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields
Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 2021
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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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Olivier J Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, and Relja Arandjelović · 2022
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Decomposing NeRF for editing via feature field distillation
Sosuke Kobayashi, Eiichi Matsumoto, and Vincent Sitzmann · 2022
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Panoptic neural fields: A semantic object-aware neural scene representation
Abhijit Kundu, Kyle Genova, Xiaoqi Yin, Alireza Fathi, Caroline Pantofaru, Leonidas J Guibas, Andrea Tagliasacchi, Frank Dellaert, and Thomas Funkhouser · 2022
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Panoptic neural fields: A semantic object-aware neural scene representation
Abhijit Kundu, Kyle Genova, Xiaoqi Yin, Alireza Fathi, Caroline Pantofaru, Leonidas J. Guibas, Andrea Tagliasacchi, Frank Dellaert, and Thomas A. Funkhouser · 2022
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Laterf: Label and text driven object radiance fields
Ashkan Mirzaei, Yash Kant, Jonathan Kelly, and Igor Gilitschenski · 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 Feature Fusion Fields: 3D distillation of self-supervised 2D image representation
Vadim Tschernezki, Iro Laina, Diane Larlus, and Andrea Vedaldi · 2022
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Dm-nerf: 3d scene geometry decomposition and manipulation from 2d images
Bing Wang, Lu Chen, and Bo Yang · 2022
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Unsupervised discovery of object radiance fields
Hong-Xing Yu, Leonidas Guibas, and Jiajun Wu · 2022
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Cmt-deeplab: Clustering mask transformers for panoptic segmentation
Qihang Yu, Huiyu Wang, Dahun Kim, Siyuan Qiao, Maxwell Collins, Yukun Zhu, Hartwig Adam, Alan Yuille, and Liang-Chieh Chen · 2022
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k-means mask transformer
Qihang Yu, Huiyu Wang, Siyuan Qiao, Maxwell Collins, Yukun Zhu, Hartwig Adam, Alan Yuille, and Liang-Chieh Chen · 2022
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Detecting twenty-thousand classes using image-level supervision
Xingyi Zhou, Rohit Girdhar, Armand Joulin, Philipp Krähenbühl, and Ishan Misra · 2022
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Coke: Contrastive learning for robust keypoint detection
Yutong Bai, Angtian Wang, Adam Kortylewski, and Alan Yuille · 2023
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NeRF-SOS: Any-view self-supervised object segmentation on complex scenes
Zhiwen Fan, Peihao Wang, Yifan Jiang, Xinyu Gong, Dejia Xu, and Zhangyang Wang · 2023
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Instance neural radiance field
Benran Hu, Junkai Huang, Yichen Liu, Yu-Wing Tai, and Chi-Keung Tang · 2023
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Lerf: Language embedded radiance fields
Justin Kerr, Chung Min Kim, Ken Goldberg, Angjoo Kanazawa, and Matthew Tancik · 2023
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Neural groundplans: Persistent neural scene representations from a single image
Prafull Sharma, Ayush Tewari, Yilun Du, Sergey Zakharov, Rares Andrei Ambrus, Adrien Gaidon, William T. Freeman, Fredo Durand, Joshua B. Tenenbaum, and Vincent Sitzmann · 2023
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Panoptic lifting for 3d scene understanding with neural fields
Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Bulò, Norman Müller, Matthias Nießner, Angela Dai, and Peter Kontschieder · 2023
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DM-neRF: 3d scene geometry decomposition and manipulation from 2d images
Bing WANG, Lu Chen, and Bo Yang · 2023
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