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To reduce the reliance on large-scale datasets, recent works in 3D segmentation resort to few-shot learning.
3d semantic parsing of large-scale indoor spaces
Armeni, I.; Sener, O.; Zamir, A. R.; Jiang, H.; Brilakis, I.; Fischer, M.; and Savarese, S. 2016 · 2016
Earlier work this paper cites.
Matching networks for one shot learning
Vinyals, O.; Blundell, C.; Lillicrap, T.; Wierstra, D.; et al. 2016 · 2016
Earlier work this paper cites.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
Dai, A.; Chang, A. X.; Savva, M.; Halber, M.; Funkhouser, T.; and Nießner, M. 2017 · 2017
Earlier work this paper cites.
Few-shot learning with graph neural networks
Garcia, V.; and Bruna, J. 2017 · 2017
Earlier work this paper cites.
One-shot learning for semantic segmentation
Shaban, A.; Bansal, S.; Liu, Z.; Essa, I.; and Boots, B. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
Earlier work this paper cites.
Edge and corner detection for unorganized 3d point clouds with application to robotic welding
Ahmed, S. M.; Tan, Y. Z.; Chew, C. M.; Al Mamun, A.; and Wong, F. S. 2018 · 2018
Earlier work this paper cites.
A lidar point cloud generator: from a virtual world to autonomous driving
Yue, X.; Wu, B.; Seshia, S. A.; Keutzer, K.; and Sangiovanni-Vincentelli, A. L. 2018 · 2018
Earlier work this paper cites.
Fast and robust 3D person detector and posture estimator for mobile robotic applications
Lewandowski, B.; Liebner, J.; Wengefeld, T.; Müller, S.; and Gross, H.-M. 2019 · 2019
Earlier work this paper cites.
Dynamic graph cnn for learning on point clouds
Wang, Y.; Sun, Y.; Liu, Z.; Sarma, S. E.; Bronstein, M. M.; and Solomon, J. M. 2019 · 2019
Earlier work this paper cites.
Deep learning on 3D point clouds
Bello, S. A.; Yu, S.; Wang, C.; Adam, J. M.; and Li, J. 2020 · 2020
Earlier work this paper cites.
xmuda: Cross-modal unsupervised domain adaptation for 3d semantic segmentation
Jaritz, M.; Vu, T.-H.; Charette, R. d.; Wirbel, E.; and Pérez, P. 2020 · 2020
Earlier work this paper cites.
Fuseseg: Lidar point cloud segmentation fusing multi-modal data
Krispel, G.; Opitz, M.; Waltner, G.; Possegger, H.; and Bischof, H. 2020 · 2020
Earlier work this paper cites.
Fourier features let networks learn high frequency functions in low dimensional domains
Tancik, M.; Srinivasan, P.; Mildenhall, B.; Fridovich-Keil, S.; Raghavan, N.; Singhal, U.; Ramamoorthi, R.; Barron, J.; and Ng, R. 2020 · 2020
Earlier work this paper cites.
Pillar-based object detection for autonomous driving
Wang, Y.; Fathi, A.; Kundu, A.; Ross, D. A.; Pantofaru, C.; Funkhouser, T.; and Solomon, J. 2020 · 2020
Cited alongside, same era.
Nerf: Representing scenes as neural radiance fields for view synthesis
Mildenhall, B.; Srinivasan, P. P.; Tancik, M.; Barron, J. T.; Ramamoorthi, R.; and Ng, R. 2021 · 2021
Cited alongside, same era.
An End-to-End Transformer Model for 3D Object Detection
Misra, I.; Girdhar, R.; and Joulin, A. 2021 · 2021
Cited alongside, same era.
Pointr: Diverse point cloud completion with geometry-aware transformers
Yu, X.; Rao, Y.; Wang, Z.; Liu, Z.; Lu, J.; and Zhou, J. 2021 · 2021
Cited alongside, same era.
Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
Zhang, R.; Fang, R.; Gao, P.; Zhang, W.; Li, K.; Dai, J.; Qiao, Y.; and Li, H. 2021 · 2021
Cited alongside, same era.
2dpass: 2d priors assisted semantic segmentation on lidar point clouds
Yan, X.; Gao, J.; Zheng, C.; Zheng, C.; Zhang, R.; Cui, S.; and Li, Z. 2022 · 2022
Later among the works it cites.
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Zhang, R.; Guo, Z.; Gao, P.; Fang, R.; Zhao, B.; Wang, D.; Qiao, Y.; and Li, H. 2022a · 2022
Later among the works it cites.
PointCLIP: Point Cloud Understanding by CLIP
Zhang, R.; Guo, Z.; Zhang, W.; Li, K.; Miao, X.; Cui, B.; Qiao, Y.; Gao, P.; and Li, H. 2022b · 2022
Later among the works it cites.
PiMAE: Point Cloud and Image Interactive Masked Autoencoders for 3D Object Detection
Chen, A.; Zhang, K.; Zhang, R.; Wang, Z.; Lu, Y.; Guo, Y.; and Zhang, S. 2023 · 2023
Closest in time.
BEV-SAN: Accurate BEV 3D Object Detection via Slice Attention Networks
Chi, X.; Liu, J.; Lu, M.; Zhang, R.; Wang, Z.; Guo, Y.; and Zhang, S. 2023 · 2023
Closest in time.
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Zhao, H.; Jiang, L.; Jia, J.; Torr, P. H.; and Koltun, V. 2021 · 2021
Cited alongside, same era.
Few-shot 3d point cloud semantic segmentation
Zhao, N.; Chua, T.-S.; and Lee, G. H. 2021 · 2021
Cited alongside, same era.
Stratified transformer for 3d point cloud segmentation
Lai, X.; Liu, J.; Jiang, L.; Wang, L.; Zhao, H.; Liu, S.; Qi, X.; and Jia, J. 2022 · 2022
Cited alongside, same era.
Primitive3d: 3d object dataset synthesis from randomly assembled primitives
Li, X.; Ding, H.; Tong, Z.; Wu, Y.; and Chee, Y. M. 2022 · 2022
Cited alongside, same era.
A review of location encoding for GeoAI: methods and applications
Mai, G.; Janowicz, K.; Hu, Y.; Gao, S.; Yan, B.; Zhu, R.; Cai, L.; and Lao, N. 2022 · 2022
Cited alongside, same era.
Bidirectional Feature Globalization for Few-shot Semantic Segmentation of 3D Point Cloud Scenes
Mao, Y.; Guo, Z.; Xiaonan, L.; Yuan, Z.; and Guo, H. 2022 · 2022
Cited alongside, same era.
Masked autoencoders for point cloud self-supervised learning
Pang, Y.; Wang, W.; Tay, F. E.; Liu, W.; Tian, Y.; and Yuan, L. 2022 · 2022
Cited alongside, same era.
Guo, Z.; Zhang, R.; Qiu, L.; Li, X.; and Heng, P. A. 2023 · 2023
Closest in time.
Prototype adaption and projection for few-and zero-shot 3d point cloud semantic segmentation
He, S.; Jiang, X.; Jiang, W.; and Ding, H. 2023 · 2023
Closest in time.
Transformer-based visual segmentation: A survey
Li, X.; Ding, H.; Zhang, W.; Yuan, H.; Pang, J.; Cheng, G.; Chen, K.; Liu, Z.; and Loy, C. C. 2023 · 2023
Closest in time.
OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding
Liu, M.; Shi, R.; Kuang, K.; Zhu, Y.; Li, X.; Han, S.; Cai, H.; Porikli, F.; and Su, H. 2023 · 2023
Closest in time.
Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding
Yang, Y.-Q.; Guo, Y.-X.; Xiong, J.-Y.; Liu, Y.; Pan, H.; Wang, P.-S.; Tong, X.; and Guo, B. 2023 · 2023
Closest in time.
Nearest Neighbors Meet Deep Neural Networks for Point Cloud Analysis
Zhang, R.; Wang, L.; Guo, Z.; and Shi, J. 2022c · 2023
Closest in time.
Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders
Zhang, R.; Wang, L.; Qiao, Y.; Gao, P.; and Li, H. 2023b · 2023
Closest in time.
Pointclip v2: Adapting clip for powerful 3d open-world learning
Zhu, X.; Zhang, R.; He, B.; Zeng, Z.; Zhang, S.; and Gao, P. 2022 · 2023
Closest in time.
Not all features matter: Enhancing few-shot clip with adaptive prior refinement
Zhu, X.; Zhang, R.; He, B.; Zhou, A.; Wang, D.; Zhao, B.; and Gao, P. 2023b · 2023
Closest in time.