Fetching the paper…
Reading the bibliography…
Unsupervised domain adaptation (UDA) is vital for alleviating the workload of labeling 3D point cloud data and mitigating the absence of labels when facing a newly defined domain.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Virtual worlds as proxy for multi-object tracking analysis
Adrien Gaidon, Qiao Wang, Yohann Cabon, and Eleonora Vig · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
Earlier work this paper cites.
Mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2017
Earlier work this paper cites.
3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens Van Der Maaten · 2018
Earlier work this paper cites.
Semantickitti: A dataset for semantic scene understanding of lidar sequences
Jens Behley, Martin Garbade, Andres Milioto, Jan Quenzel, Sven Behnke, Cyrill Stachniss, and Jurgen Gall · 2019
Earlier work this paper cites.
Bidirectional learning for domain adaptation of semantic segmentation
Yunsheng Li, Lu Yuan, and Nuno Vasconcelos · 2019
Earlier work this paper cites.
Cutmix: Regularization strategy to train strong classifiers with localizable features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
Earlier work this paper cites.
nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
Earlier work this paper cites.
A2D2: Audi Autonomous Driving Dataset
Jakob Geyer, Yohannes Kassahun, Mentar Mahmudi, Xavier Ricou, Rupesh Durgesh, Andrew S. Chung, Lorenz Hauswald, Viet Hoang Pham, Maximilian Mühlegg, Sebastian Dorn, Tiffany Fernandez, Martin Jänicke, Sudesh Mirashi, Chiragkumar Savani, Martin Sturm, Oleksandr Vorobiov, Martin Oelker, Sebastian Garreis, and Peter Schuberth · 2020
Earlier work this paper cites.
xmuda: Cross-modal unsupervised domain adaptation for 3d semantic segmentation
Maximilian Jaritz, Tuan-Hung Vu, Raoul de Charette, Emilie Wirbel, and Patrick Pérez · 2020
Earlier work this paper cites.
Learning texture invariant representation for domain adaptation of semantic segmentation
Myeongjin Kim and Hyeran Byun · 2020
Earlier work this paper cites.
Unsupervised intra-domain adaptation for semantic segmentation through self-supervision
Fei Pan, Inkyu Shin, Francois Rameau, Seokju Lee, and In So Kweon · 2020
Earlier work this paper cites.
Unsupervised domain adaptation in semantic segmentation: A review
Marco Toldo, Andrea Maracani, Umberto Michieli, and Pietro Zanuttigh · 2020
Earlier work this paper cites.
Multi-path region mining for weakly supervised 3d semantic segmentation on point clouds
Jiacheng Wei, Guosheng Lin, Kim-Hui Yap, Tzu-Yi Hung, and Lihua Xie · 2020
Earlier work this paper cites.
Dual mixup regularized learning for adversarial domain adaptation
Yuan Wu, Diana Inkpen, and Ahmed El-Roby · 2020
Earlier work this paper cites.
Adversarial domain adaptation with domain mixup
Minghao Xu, Jian Zhang, Bingbing Ni, Teng Li, Chengjie Wang, Qi Tian, and Wenjun Zhang · 2020
Cited alongside, same era.
Fda: Fourier domain adaptation for semantic segmentation
Yanchao Yang and Stefano Soatto · 2020
Cited alongside, same era.
Joint adversarial learning for domain adaptation in semantic segmentation
Yixin Zhang and Zilei Wang · 2020
Cited alongside, same era.
Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges
Di Feng, Christian Haase-Schütz, Lars Rosenbaum, Heinz Hertlein, Claudius Gläser, Fabian Timm, Werner Wiesbeck, and Klaus Dietmayer · 2021
Cited alongside, same era.
Dsp: Dual soft-paste for unsupervised domain adaptive semantic segmentation
Li Gao, Jing Zhang, Lefei Zhang, and Dacheng Tao · 2021
Cited alongside, same era.
Cross-modal learning for domain adaptation in 3d semantic segmentation
Maximilian Jaritz, Tuan-Hung Vu, Raoul De Charette, Émilie Wirbel, and Patrick Pérez · 2022
Later among the works it cites.
Unsupervised domain adaptation in lidar semantic segmentation with self-supervision and gated adapters
Mrigank Rochan, Shubhra Aich, Eduardo R Corral-Soto, Amir Nabatchian, and Bingbing Liu · 2022
Later among the works it cites.
Language-grounded indoor 3d semantic segmentation in the wild
David Rozenberszki, Or Litany, and Angela Dai · 2022
Later among the works it cites.
Cosmix: Compositional semantic mix for domain adaptation in 3d lidar segmentation
Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni, Nicu Sebe, Elisa Ricci, and Fabio Poiesi · 2022
Later among the works it cites.
Mm-tta: Multi-modal test-time adaptation for 3d semantic segmentation
Inkyu Shin, Yi-Hsuan Tsai, Bingbing Zhuang, Samuel Schulter, Buyu Liu, Sparsh Garg, In So Kweon, and Kuk-Jin Yoon · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Qingyong Hu, Bo Yang, Sheikh Khalid, Wen Xiao, Niki Trigoni, and Andrew Markham · 2021
Cited alongside, same era.
Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig · 2021
Cited alongside, same era.
Guided point contrastive learning for semi-supervised point cloud semantic segmentation
Li Jiang, Shaoshuai Shi, Zhuotao Tian, Xin Lai, Shu Liu, Chi-Wing Fu, and Jiaya Jia · 2021
Cited alongside, same era.
Adversarial unsupervised domain adaptation for 3d semantic segmentation with multi-modal learning
Wei Liu, Zhiming Luo, Yuanzheng Cai, Ying Yu, Yang Ke, José Marcato Junior, Wesley Nunes Gonçalves, and Jonathan Li · 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.
Sparse-to-dense feature matching: Intra and inter domain cross-modal learning in domain adaptation for 3d semantic segmentation
Duo Peng, Yinjie Lei, Wen Li, Pingping Zhang, and Yulan Guo · 2021
Cited alongside, same era.
Semantic segmentation for real point cloud scenes via bilateral augmentation and adaptive fusion
Shi Qiu, Saeed Anwar, and Nick Barnes · 2021
Cited alongside, same era.
Polarmix: A general data augmentation technique for lidar point clouds
Aoran Xiao, Jiaxing Huang, Dayan Guan, Kaiwen Cui, Shijian Lu, and Ling Shao · 2022
Later among the works it cites.
Exploiting the complementarity of 2d and 3d networks to address domain-shift in 3d semantic segmentation
Adriano Cardace, Pierluigi Zama Ramirez, Samuele Salti, and Luigi Di Stefano · 2023
Later among the works it cites.
Cross-modal & cross-domain learning for unsupervised lidar semantic segmentation
Yiyang Chen, Shanshan Zhao, Changxing Ding, Liyao Tang, Chaoyue Wang, and Dacheng Tao · 2023
Later among the works it cites.
Segment anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick · 2023
Later among the works it cites.
Lasermix for semi-supervised lidar semantic segmentation
Lingdong Kong, Jiawei Ren, Liang Pan, and Ziwei Liu · 2023
Later among the works it cites.
Segment any point cloud sequences by distilling vision foundation models
Youquan Liu, Lingdong Kong, Jun Cen, Runnan Chen, Wenwei Zhang, Liang Pan, Kai Chen, and Ziwei Liu · 2023
Later among the works it cites.
Compositional semantic mix for domain adaptation in point cloud segmentation
Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni, Nicu Sebe, Fabio Poiesi, and Elisa Ricci · 2023
Later among the works it cites.
Domain generalization of 3d semantic segmentation in autonomous driving
Jules Sanchez, Jean-Emmanuel Deschaud, and François Goulette · 2023
Later among the works it cites.
Llama: Open and efficient foundation language models. corr, abs/2302.13971, 2023. doi: 10.48550
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
Later among the works it cites.
Gpt-4: A new era of artificial intelligence in medicine
Ethan Waisberg, Joshua Ong, Mouayad Masalkhi, Sharif Amit Kamran, Nasif Zaman, Prithul Sarker, Andrew G Lee, and Alireza Tavakkoli · 2023
Later among the works it cites.
When 3d bounding-box meets sam: Point cloud instance segmentation with weak-and-noisy supervision
Qingtao Yu, Heming Du, Chen Liu, and Xin Yu · 2023
Later among the works it cites.
Growsp: Unsupervised semantic segmentation of 3d point clouds
Zihui Zhang, Bo Yang, Bing Wang, and Bo Li · 2023
Later among the works it cites.