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The development of 2D foundation models for image segmentation has been significantly advanced by the Segment Anything Model (SAM).
Shapenet: An information-rich 3d model repository, 2015
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
Earlier work this paper cites.
3d semantic parsing of large-scale indoor spaces
Iro Armeni, Ozan Sener, Amir R Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese · 2016
Earlier work this paper cites.
Scenenn: A scene meshes dataset with annotations
Binh-Son Hua, Quang-Hieu Pham, Duc Thanh Nguyen, Minh-Khoi Tran, Lap-Fai Yu, and Sai-Kit Yeung · 2016
Earlier work this paper cites.
V-net: Fully convolutional neural networks for volumetric medical image segmentation
Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi · 2016
Earlier work this paper cites.
A scalable active framework for region annotation in 3d shape collections
Li Yi, Vladimir G Kim, Duygu Ceylan, I-Chao Shen, Mengyan Yan, Hao Su, Cewu Lu, Qixing Huang, Alla Sheffer, and Leonidas Guibas · 2016
Earlier work this paper cites.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
Earlier work this paper cites.
Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
Earlier work this paper cites.
3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens Van Der Maaten · 2018
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Partnet: A large-scale benchmark for fine-grained and hierarchical part-level 3d object understanding
Kaichun Mo, Shilin Zhu, Angel X Chang, Li Yi, Subarna Tripathi, Leonidas J Guibas, and Hao Su · 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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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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Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan Barron, and Ren Ng · 2020
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Sapien: A simulated part-based interactive environment
Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, et al · 2020
Earlier work this paper cites.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
Cited alongside, same era.
Brepnet: A topological message passing system for solid models
Joseph G. Lambourne, Karl D.D. Willis, Pradeep Kumar Jayaraman, Aditya Sanghi, Peter Meltzer, and Hooman Shayani · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Point transformer
Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip HS Torr, and Vladlen Koltun · 2021
Cited alongside, same era.
Grounded language-image pre-training
Liunian Harold Li, Pengchuan Zhang, Haotian Zhang, Jianwei Yang, Chunyuan Li, Yiwu Zhong, Lijuan Wang, Lu Yuan, Lei Zhang, Jenq-Neng Hwang, et al · 2022
Cited alongside, same era.
Mask3D: Mask Transformer for 3D Semantic Instance Segmentation
Jonas Schult, Francis Engelmann, Alexander Hermans, Or Litany, Siyu Tang, and Bastian Leibe · 2023
Later among the works it cites.
Generalizable visual reinforcement learning with segment anything model
Ziyu Wang, Yanjie Ze, Yifei Sun, Zhecheng Yuan, and Huazhe Xu · 2023
Later among the works it cites.
Sampro3d: Locating sam prompts in 3d for zero-shot scene segmentation
Mutian Xu, Xingyilang Yin, Lingteng Qiu, Yang Liu, Xin Tong, and Xiaoguang Han · 2023
Later among the works it cites.
Sam3d: Segment anything in 3d scenes
Yunhan Yang, Xiaoyang Wu, Tong He, Hengshuang Zhao, and Xihui Liu · 2023
Later among the works it cites.
Agile3d: Attention guided interactive multi-object 3d segmentation
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KITTI-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d
Yiyi Liao, Jun Xie, and Andreas Geiger · 2022
Cited alongside, same era.
Point transformer v2: Grouped vector attention and partition-based pooling
Xiaoyang Wu, Yixing Lao, Li Jiang, Xihui Liu, and Hengshuang Zhao · 2022
Cited alongside, same era.
Easyhec: Accurate and automatic hand-eye calibration via differentiable rendering and space exploration
Linghao Chen, Yuzhe Qin, Xiaowei Zhou, and Hao Su · 2023
Cited alongside, same era.
3d-llm: Injecting the 3d world into large language models
Yining Hong, Haoyu Zhen, Peihao Chen, Shuhong Zheng, Yilun Du, Zhenfang Chen, and Chuang Gan · 2023
Cited alongside, same era.
Segment3d: Learning fine-grained class-agnostic 3d segmentation without manual labels
Rui Huang, Songyou Peng, Ayca Takmaz, Federico Tombari, Marc Pollefeys, Shiji Song, Gao Huang, and Francis Engelmann · 2023
Cited alongside, same era.
Segment anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
Cited alongside, same era.
Interactive object segmentation in 3d point clouds
Theodora Kontogianni, Ekin Celikkan, Siyu Tang, and Konrad Schindler · 2023
Cited alongside, same era.
Yuanwen Yue, Sabarinath Mahadevan, Jonas Schult, Francis Engelmann, Bastian Leibe, Konrad Schindler, and Theodora Kontogianni · 2023
Later among the works it cites.
Segment anything in 3d with radiance fields, 2024
Jiazhong Cen, Jiemin Fang, Zanwei Zhou, Chen Yang, Lingxi Xie, Xiaopeng Zhang, Wei Shen, and Qi Tian · 2024
Closest in time.
An embodied generalist agent in 3d world
Jiangyong Huang, Silong Yong, Xiaojian Ma, Xiongkun Linghu, Puhao Li, Yan Wang, Qing Li, Song-Chun Zhu, Baoxiong Jia, and Siyuan Huang · 2024
Closest in time.
Openshape: Scaling up 3d shape representation towards open-world understanding
Minghua Liu, Ruoxi Shi, Kaiming Kuang, Yinhao Zhu, Xuanlin Li, Shizhong Han, Hong Cai, Fatih Porikli, and Hao Su · 2024
Closest in time.
Better call sal: Towards learning to segment anything in lidar
Aljoša Ošep, Tim Meinhardt, Francesco Ferroni, Neehar Peri, Deva Ramanan, and Laura Leal-Taixé · 2024
Closest in time.
Openmask3d: Open-vocabulary 3d instance segmentation
Ayca Takmaz, Elisabetta Fedele, Robert Sumner, Marc Pollefeys, Federico Tombari, and Francis Engelmann · 2024
Closest in time.
Efficientvit-sam: Accelerated segment anything model without performance loss
Zhuoyang Zhang, Han Cai, and Song Han · 2024
Closest in time.
Serf: Fine-grained interactive 3d segmentation and editing with radiance fields, 2024
Kaichen Zhou, Lanqing Hong, Enze Xie, Yongxin Yang, Zhenguo Li, and Wei Zhang · 2024
Closest in time.