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Advancements in 3D instance segmentation have traditionally been tethered to the availability of annotated datasets, limiting their application to a narrow spectrum of object categories.
Efficient graph-based image segmentation
Pedro F Felzenszwalb and Daniel P Huttenlocher · 2004
Earlier work this paper cites.
Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
Earlier work this paper cites.
Matterport3d: Learning from rgb-d data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 2017
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
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Accelerated hierarchical density based clustering
Leland McInnes and John Healy · 2017
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3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens Van Der Maaten · 2018
Earlier work this paper cites.
Pointcnn: Convolution on x-transformed points
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018
Earlier work this paper cites.
Fully-convolutional point networks for large-scale point clouds
Dario Rethage, Johanna Wald, Jurgen Sturm, Nassir Navab, and Federico Tombari · 2018
Earlier work this paper cites.
Sgpn: Similarity group proposal network for 3d point cloud instance segmentation
Weiyue Wang, Ronald Yu, Qiangui Huang, and Ulrich Neumann · 2018
Earlier work this paper cites.
4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
Earlier work this paper cites.
3d-sis: 3d semantic instance segmentation of rgb-d scans
Ji Hou, Angela Dai, and Matthias Nießner · 2019
Earlier work this paper cites.
Kpconv: Flexible and deformable convolution for point clouds
Hugues Thomas, Charles R Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, and Leonidas J Guibas · 2019
Earlier work this paper cites.
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
Earlier work this paper cites.
Pointconv: Deep convolutional networks on 3d point clouds
Wenxuan Wu, Zhongang Qi, and Li Fuxin · 2019
Earlier work this paper cites.
Occuseg: Occupancy-aware 3d instance segmentation
Lei Han, Tian Zheng, Lan Xu, and Lu Fang · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
Virtual multi-view fusion for 3d semantic segmentation
Abhijit Kundu, Xiaoqi Yin, Alireza Fathi, David Ross, Brian Brewington, Thomas Funkhouser, and Caroline Pantofaru · 2020
Earlier work this paper cites.
Scf-net: Learning spatial contextual features for large-scale point cloud segmentation
Siqi Fan, Qiulei Dong, Fenghua Zhu, Yisheng Lv, Peijun Ye, and Fei-Yue Wang · 2021
Cited alongside, same era.
Open-vocabulary object detection via vision and language knowledge distillation
Xiuye Gu, Tsung-Yi Lin, Weicheng Kuo, and Yin Cui · 2021
Cited alongside, same era.
Instance segmentation in 3d scenes using semantic superpoint tree networks
Zhihao Liang, Zhihao Li, Songcen Xu, Mingkui Tan, and Kui Jia · 2021
Cited alongside, same era.
Mix3d: Out-of-context data augmentation for 3d scenes
Alexey Nekrasov, Jonas Schult, Or Litany, Bastian Leibe, and Francis Engelmann · 2021
Cited alongside, same era.
Fine-grained image captioning with clip reward
Jaemin Cho, Seunghyun Yoon, Ajinkya Kale, Franck Dernoncourt, Trung Bui, and Mohit Bansal · 2022
Cited alongside, same era.
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick · 2023
Closest in time.
Top-down beats bottom-up in 3d instance segmentation
Maksim Kolodiazhnyi, Danila Rukhovich, Anna Vorontsova, and Anton Konushin · 2023
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Semantic-sam: Segment and recognize anything at any granularity
Feng Li, Hao Zhang, Peize Sun, Xueyan Zou, Shilong Liu, Jianwei Yang, Chunyuan Li, Lei Zhang, and Jianfeng Gao · 2023
Closest in time.
Open-vocabulary semantic segmentation with mask-adapted clip
Feng Liang, Bichen Wu, Xiaoliang Dai, Kunpeng Li, Yinan Zhao, Hang Zhang, Peizhao Zhang, Peter Vajda, and Diana Marculescu · 2023
Closest in time.
Gridclip: One-stage object detection by grid-level clip representation learning
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Scaling open-vocabulary image segmentation with image-level labels
Golnaz Ghiasi, Xiuye Gu, Yin Cui, and Tsung-Yi Lin · 2022
Cited alongside, same era.
Learning superpoint graph cut for 3d instance segmentation
Le Hui, Linghua Tang, Yaqi Shen, Jin Xie, and Jian Yang · 2022
Cited alongside, same era.
Decomposing nerf for editing via feature field distillation
Sosuke Kobayashi, Eiichi Matsumoto, and Vincent Sitzmann · 2022
Cited alongside, same era.
Unsupervised class-agnostic instance segmentation of 3d lidar data for autonomous vehicles
Lucas Nunes, Xieyuanli Chen, Rodrigo Marcuzzi, Aljosa Osep, Laura Leal-Taixé, Cyrill Stachniss, and Jens Behley · 2022
Cited alongside, same era.
Language-grounded indoor 3d semantic segmentation in the wild
David Rozenberszki, Or Litany, and Angela Dai · 2022
Cited alongside, same era.
Softgroup++: Scalable 3d instance segmentation with octree pyramid grouping
Thang Vu, Kookhoi Kim, Tung M Luu, Thanh Nguyen, Junyeong Kim, and Chang D Yoo · 2022
Cited alongside, same era.
Clip-diffusion-lm: Apply diffusion model on image captioning
Shitong Xu · 2022
Cited alongside, same era.
Jiayi Lin and Shaogang Gong · 2023
Closest in time.
Ovir-3d: Open-vocabulary 3d instance retrieval without training on 3d data
Shiyang Lu, Haonan Chang, Eric Pu Jing, Abdeslam Boularias, and Kostas Bekris · 2023
Closest in time.
Open3dis: Open-vocabulary 3d instance segmentation with 2d mask guidance
Phuc DA Nguyen, Tuan Duc Ngo, Chuang Gan, Evangelos Kalogerakis, Anh Tran, Cuong Pham, and Khoi Nguyen · 2023
Closest in time.
Openscene: 3d scene understanding with open vocabularies
Songyou Peng, Kyle Genova, Chiyu ”Max” Jiang, Andrea Tagliasacchi, Marc Pollefeys, and Thomas Funkhouser · 2023
Closest in time.
Unscene3d: Unsupervised 3d instance segmentation for indoor scenes
David Rozenberszki, Or Litany, and Angela Dai · 2023
Closest in time.
Mask3d: Mask transformer for 3d semantic instance segmentation
Jonas Schult, Francis Engelmann, Alexander Hermans, Or Litany, Siyu Tang, and Bastian Leibe · 2023
Closest in time.
Superpoint transformer for 3d scene instance segmentation
Jiahao Sun, Chunmei Qing, Junpeng Tan, and Xiangmin Xu · 2023
Closest in time.
OpenMask3D: Open-Vocabulary 3D Instance Segmentation
Ayça Takmaz, Elisabetta Fedele, Robert W. Sumner, Marc Pollefeys, Federico Tombari, and Francis Engelmann · 2023
Closest in time.
Sam3d: Segment anything in 3d scenes
Yunhan Yang, Xiaoyang Wu, Tong He, Hengshuang Zhao, and Xihui Liu · 2023
Closest in time.
Scannet++: A high-fidelity dataset of 3d indoor scenes
Chandan Yeshwanth, Yueh-Cheng Liu, Matthias Nießner, and Angela Dai · 2023
Closest in time.
Growsp: Unsupervised semantic segmentation of 3d point clouds
Zihui Zhang, Bo Yang, Bing Wang, and Bo Li · 2023
Closest in time.
Mi Yan, Jiazhao Zhang, Yan Zhu, and He Wang · 2024
Closest in time.