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ORCIDWeiming Zhi
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2020 – today
- 2024
[j2]Weiming Zhi
, Haozhan Tang, Tianyi Zhang, Matthew Johnson-Roberson:
Unifying Representation and Calibration With 3D Foundation Models. IEEE Robotics Autom. Lett. 9(10): 8953-8960 (2024)- [c16]Weiming Zhi, Tianyi Zhang, Matthew Johnson-Roberson:
Instructing Robots by Sketching: Learning from Demonstration via Probabilistic Diagrammatic Teaching. ICRA 2024: 15047-15053 - [c15]Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra:
Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning. ICRA 2024: 15068-15075 - [i19]Herbert Wright, Weiming Zhi, Matthew Johnson-Roberson, Tucker Hermans:
V-PRISM: Probabilistic Mapping of Unknown Tabletop Scenes. CoRR abs/2403.08106 (2024) - [i18]Tianyi Zhang, Kaining Huang, Weiming Zhi, Matthew Johnson-Roberson:
DarkGS: Learning Neural Illumination and 3D Gaussians Relighting for Robotic Exploration in the Dark. CoRR abs/2403.10814 (2024) - [i17]Qilin Sun, Weiming Zhi, Tianyi Zhang, Matthew Johnson-Roberson:
Diagrammatic Instructions to Specify Spatial Objectives and Constraints with Applications to Mobile Base Placement. CoRR abs/2403.12465 (2024) - [i16]Weiming Zhi, Haozhan Tang, Tianyi Zhang, Matthew Johnson-Roberson:
Unifying Scene Representation and Hand-Eye Calibration with 3D Foundation Models. CoRR abs/2404.11683 (2024) - [i15]Tianyi Zhang, Weiming Zhi, Kaining Huang, Joshua Mangelson, Corina Barbalata, Matthew Johnson-Roberson:
RecGS: Removing Water Caustic with Recurrent Gaussian Splatting. CoRR abs/2407.10318 (2024) - [i14]Weiming Zhi, Haozhan Tang, Tianyi Zhang, Matthew Johnson-Roberson:
3D Foundation Models Enable Simultaneous Geometry and Pose Estimation of Grasped Objects. CoRR abs/2407.10331 (2024) - [i13]Weiming Zhi:
Learning to Represent Surroundings, Anticipate Motion and Take Informed Actions in Unstructured Environments. CoRR abs/2407.10383 (2024) - [i12]Jiaxi Zheng, Guangmin Dai, Botao He, Zhaoyang Mu, Zhaochen Meng, Tianyi Zhang, Weiming Zhi, Dixia Fan:
ModCube: Modular, Self-Assembling Cubic Underwater Robot. CoRR abs/2409.15627 (2024) - 2023
- [c14]Weiming Zhi, Iretiayo Akinola, Karl Van Wyk, Nathan D. Ratliff, Fabio Ramos:
Global and Reactive Motion Generation with Geometric Fabric Command Sequences. ICRA 2023: 939-945 - [i11]Weiming Zhi, Tianyi Zhang, Matthew Johnson-Roberson:
Learning from Demonstration via Probabilistic Diagrammatic Teaching. CoRR abs/2309.03835 (2023) - [i10]Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra:
Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning. CoRR abs/2309.09021 (2023) - [i9]Weiming Zhi, Kangni Liu, Tianyi Zhang, Matthew Johnson-Roberson:
Learning Orbitally Stable Systems for Diagrammatically Teaching. CoRR abs/2309.10298 (2023) - 2022
- [c13]Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos:
Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks. ICML 2022: 27060-27074 - [c12]Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos:
Diffeomorphic Transforms for Generalised Imitation Learning. L4DC 2022: 508-519 - [i8]Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos:
L4KDE: Learning for KinoDynamic Tree Expansion. CoRR abs/2203.00975 (2022) - 2021
- [c11]Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos:
Parallelised Diffeomorphic Sampling-based Motion Planning. CoRL 2021: 81-90 - [c10]Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos:
Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements. ICRA 2021: 8459-8464 - [c9]Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos:
Trajectory Generation in New Environments from Past Experiences. IROS 2021: 7911-7918 - [c8]Weiming Zhi, Lionel Ott, Fabio Ramos:
Probabilistic Trajectory Prediction with Structural Constraints. IROS 2021: 9849-9856 - [i7]Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos:
Learning ODEs via Diffeomorphisms for Fast and Robust Integration. CoRR abs/2107.01650 (2021) - [i6]Weiming Zhi, Lionel Ott, Fabio Ramos:
Probabilistic Trajectory Prediction with Structural Constraints. CoRR abs/2107.04193 (2021) - [i5]Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos:
Parallelised Diffeomorphic Sampling-based Motion Planning. CoRR abs/2108.11775 (2021) - 2020
- [i4]Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos:
Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements. CoRR abs/2011.06235 (2020)
2010 – 2019
- 2019
- [j1]Weiming Zhi, Ransalu Senanayake, Lionel Ott, Fabio Ramos:
Spatiotemporal Learning of Directional Uncertainty in Urban Environments With Kernel Recurrent Mixture Density Networks. IEEE Robotics Autom. Lett. 4(4): 4306-4313 (2019) - [c7]Weiming Zhi, Lionel Ott, Fabio Ramos:
Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction. CoRL 2019: 1405-1414 - [c6]Weiming Zhi, Lionel Ott, Ransalu Senanayake, Fabio Ramos:
Continuous Occupancy Map Fusion with Fast Bayesian Hilbert Maps. ICRA 2019: 4111-4117 - [i3]Weiming Zhi, Lionel Ott, Fabio Ramos:
Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction. CoRR abs/1907.05127 (2019) - [i2]Tin Lai, Weiming Zhi, Fabio Ramos:
Occ-Traj120: Occupancy Maps with Associated Trajectories. CoRR abs/1909.02333 (2019) - [i1]Weiming Zhi, Tin Lai, Lionel Ott, Gilad Francis, Fabio Ramos:
OCTNet: Trajectory Generation in New Environments from Past Experiences. CoRR abs/1909.11337 (2019) - 2017
- [c5]Jianlong Zhou, Zelin Li, Weiming Zhi, Bin Liang, Daniel Aaron Moses, Laughlin Dawes:
Using Convolutional Neural Networks and Transfer Learning for Bone Age Classification. DICTA 2017: 1-6 - [c4]Zhicheng Lu, Yuk Ying Chung, Henry Wing Fung Yeung, Seid Miad Zandavi, Weiming Zhi, Wei-Chang Yeh:
Using Hidden Markov Model to Predict Human Actions with Swarm Intelligence. ICONIP (4) 2017: 21-30 - [c3]Seid Miad Zandavi, Feng Sha, Vera Yuk Ying Chung, Zhicheng Lu, Weiming Zhi:
A Novel Ant Colony Detection Using Multi-Region Histogram for Object Tracking. ICONIP (3) 2017: 25-33 - [c2]Weiming Zhi, Zhenghao Chen, Henry Wing Fung Yeung, Zhicheng Lu, Seid Miad Zandavi, Yuk Ying Chung:
Layer Removal for Transfer Learning with Deep Convolutional Neural Networks. ICONIP (2) 2017: 460-469 - [c1]Weiming Zhi, Henry Wing Fung Yeung, Zhenghao Chen, Seid Miad Zandavi, Zhicheng Lu, Yuk Ying Chung:
Using Transfer Learning with Convolutional Neural Networks to Diagnose Breast Cancer from Histopathological Images. ICONIP (4) 2017: 669-676
Coauthor Index
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last updated on 2024-10-17 21:26 CEST by the dblp team
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