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Publication search results
found 157 matches
- 2024
- Jiajia Lu, Wun-She Yap, Kok-Chin Khor:
PointADAM: Unsupervised Adversarial Domain Adaptation on Point Clouds With Metric Learning via Compact Feature Representation. IEEE Access 12: 77486-77500 (2024) - Siddharth Katageri, Arkadipta De, Chaitanya Devaguptapu, V. S. S. V. Prasad, Charu Sharma, Manohar Kaul:
Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptation. WACV 2024: 2930-2939 - Jie Liu, Wenzhe Yin, Haochen Wang, Yunlu Chen, Jan-Jakob Sonke, Efstratios Gavves:
Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud Segmentation. CoRR abs/2401.16051 (2024) - 2023
- Shaolei Liu, Xiaoyuan Luo, Kexue Fu, Manning Wang, Zhijian Song:
A learnable self-supervised task for unsupervised domain adaptation on point cloud classification and segmentation. Frontiers Comput. Sci. 17(6): 176708 (2023) - Radek Silhavy, Miroslav Bures, Melchizedek Alipio, Petr Silhavy:
More Accurate Cost Estimation for Internet of Things Projects by Adaptation of Use Case Points Methodology. IEEE Internet Things J. 10(21): 19312-19327 (2023) - Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni, Nicu Sebe, Fabio Poiesi, Elisa Ricci:
Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 14234-14247 (2023) - Jintao Chen, Yan Zhang, Kun Huang, Feifan Ma, Zhuangbin Tan, Zheyu Xu:
Self-Supervised Boundary Point Prediction Task for Point Cloud Domain Adaptation. IEEE Robotics Autom. Lett. 8(9): 5878-5885 (2023) - Jieqi Shi, Peiliang Li, Xiaozhi Chen, Shaojie Shen:
You Only Label Once: 3D Box Adaptation From Point Cloud to Image With Semi-Supervised Learning. IEEE Robotics Autom. Lett. 8(10): 6811-6818 (2023) - Sebastian Huch, Markus Lienkamp:
Towards Minimizing the LiDAR Sim-to-Real Domain Shift: Object-Level Local Domain Adaptation for 3D Point Clouds of Autonomous Vehicles. Sensors 23(24): 9913 (2023) - Hojin Yoo, Kyungkoo Jun:
Point Cloud Classification by Domain Adaptation Using Recycling Max Pooling and Cutting Plane Identification. Sensors 23(3): 1177 (2023) - Chao Wang, Huitao Huang, Huimin Pan:
A constrained many-objective evolutionary algorithm with learning vector quantization-based reference point adaptation. Swarm Evol. Comput. 82: 101359 (2023) - Haoyu Zhao, Qi Wang, Guowei Zhan, Weidong Min, Yi Zou, Shimiao Cui:
Need Only One More Point (NOOMP): Perspective Adaptation Crowd Counting in Complex Scenes. IEEE Trans. Multim. 25: 1414-1426 (2023) - Xin Kong, Shifeng Xia, Ningzhong Liu, Mingqiang Wei:
GADA-SegNet: gated attentive domain adaptation network for semantic segmentation of LiDAR point clouds. Vis. Comput. 39(6): 2471-2481 (2023) - Yan Wang, Junbo Yin, Wei Li, Pascal Frossard, Ruigang Yang, Jianbing Shen:
SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud. AAAI 2023: 2707-2715 - Chun-Chieh Ku, Tsung-Yu Chen, Shang-Hong Lai:
Boosting Unsupervised Domain Adaptation for 3D Object Detection in Point Clouds with 2D Image Semantic Information. CASE 2023: 1-6 - Guangrui Li, Guoliang Kang, Xiaohan Wang, Yunchao Wei, Yi Yang:
Adversarially Masking Synthetic to Mimic Real: Adaptive Noise Injection for Point Cloud Segmentation Adaptation. CVPR 2023: 20464-20474 - Ashish Sinha, Jonghyun Choi:
MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds. CVPR Workshops 2023: 4767-4777 - Fan Wang, Zhongyi Han, Zhiyan Zhang, Rundong He, Yilong Yin:
MHPL: Minimum Happy Points Learning for Active Source Free Domain Adaptation. CVPR 2023: 20008-20018 - Suyi Chen, Hao Xu, Ru Li, Guanghui Liu, Chi-Wing Fu, Shuaicheng Liu:
SIRA-PCR: Sim-to-Real Adaptation for 3D Point Cloud Registration. ICCV 2023: 14348-14359 - Ahmed Hatem, Yiming Qian, Yang Wang:
Point-TTA: Test-Time Adaptation for Point Cloud Registration Using Multitask Meta-Auxiliary Learning. ICCV 2023: 16448-16458 - Awet Haileslassie Gebrehiwot, David Hurych, Karel Zimmermann, Patrick Pérez, Tomás Svoboda:
T-UDA: Temporal Unsupervised Domain Adaptation in Sequential Point Clouds. IROS 2023: 7643-7650 - Ahmed Hatem, Yiming Qian, Yang Wang:
Test-Time Adaptation for Point Cloud Upsampling Using Meta-Learning. IROS 2023: 1284-1291 - Liang Zhao, Meng Sun, Wei Jie Lv, Xin Yu Zhang, Long Zeng:
Domain Adaptation on Point Clouds for 6D Pose Estimation in Bin-Picking Scenarios. IROS 2023: 2925-2931 - Sungsu Hur, Inkyu Shin, Kwanyong Park, Sanghyun Woo, In So Kweon:
Learning Classifiers of Prototypes and Reciprocal Points for Universal Domain Adaptation. WACV 2023: 531-540 - Dominic Laniewski, Nils Aschenbruck:
Reinforcement Learning-Based Rate Adaptation for Point Cloud Streaming. WF-IoT 2023: 1-6 - Radek Silhavy, Melchizedek Alipio, Miroslav Bures, Petr Silhavy:
Case studies - More Accurate Cost Estimation for Internet of Things Projects by Adaptation of Use Case Points Methodology. IEEE DataPort, 2023 - Ashish Sinha, Jonghyun Choi:
MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds. CoRR abs/2304.01554 (2023) - Siddharth Katageri, Arkadipta De, Chaitanya Devaguptapu, VSSV Prasad, Charu Sharma, Manohar Kaul:
Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptation. CoRR abs/2308.14126 (2023) - Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni, Nicu Sebe, Fabio Poiesi, Elisa Ricci:
Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation. CoRR abs/2308.14619 (2023) - Ahmed Hatem, Yiming Qian, Yang Wang:
Point-TTA: Test-Time Adaptation for Point Cloud Registration Using Multitask Meta-Auxiliary Learning. CoRR abs/2308.16481 (2023)
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