Weiming Zhi

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 35

Top Topics

Motion Prediction

Urban Environments

Past Experience

Convolutional Neural Networks

Top Venues

Publications

Weiming Zhi, Tianyi Zhang, Matthew Johnson-Roberson
Instructing Robots by Sketching: Learning from Demonstration via Probabilistic Diagrammatic Teaching. ICRA (2024)
Qilin Sun, Weiming Zhi, Tianyi Zhang, Matthew Johnson-Roberson
Diagrammatic Instructions to Specify Spatial Objectives and Constraints with Applications to Mobile Base Placement. CoRR (2024)
Tianyi Zhang, Weiming Zhi, Kaining Huang, Joshua Mangelson, Corina Barbalata, Matthew Johnson-Roberson
RecGS: Removing Water Caustic with Recurrent Gaussian Splatting. CoRR (2024)
Weiming Zhi
Learning to Represent Surroundings, Anticipate Motion and Take Informed Actions in Unstructured Environments. CoRR (2024)
Herbert Wright, Weiming Zhi, Matthew Johnson-Roberson, Tucker Hermans
V-PRISM: Probabilistic Mapping of Unknown Tabletop Scenes. CoRR (2024)
Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra
Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning. ICRA (2024)
Weiming Zhi, Haozhan Tang, Tianyi Zhang, Matthew Johnson-Roberson
Unifying Scene Representation and Hand-Eye Calibration with 3D Foundation Models. CoRR (2024)
Tianyi Zhang, Kaining Huang, Weiming Zhi, Matthew Johnson-Roberson
DarkGS: Learning Neural Illumination and 3D Gaussians Relighting for Robotic Exploration in the Dark. CoRR (2024)
Weiming Zhi, Haozhan Tang, Tianyi Zhang, Matthew Johnson-Roberson
3D Foundation Models Enable Simultaneous Geometry and Pose Estimation of Grasped Objects. CoRR (2024)
Weiming Zhi, Kangni Liu, Tianyi Zhang, Matthew Johnson-Roberson
Learning Orbitally Stable Systems for Diagrammatically Teaching. CoRR (2023)
Weiming Zhi, Tianyi Zhang, Matthew Johnson-Roberson
Learning from Demonstration via Probabilistic Diagrammatic Teaching. CoRR (2023)
Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra
Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning. CoRR (2023)
Weiming Zhi, Iretiayo Akinola, Karl Van Wyk, Nathan D. Ratliff, Fabio Ramos
Global and Reactive Motion Generation with Geometric Fabric Command Sequences. ICRA (2023)
Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos
Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks. ICML (2022)
Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos
Diffeomorphic Transforms for Generalised Imitation Learning. L4DC (2022)
Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos
L4KDE: Learning for KinoDynamic Tree Expansion. CoRR (2022)
Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos
Parallelised Diffeomorphic Sampling-based Motion Planning. CoRR (2021)
Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos
Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements. ICRA (2021)
Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos
Parallelised Diffeomorphic Sampling-based Motion Planning. CoRL (2021)
Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos
Trajectory Generation in New Environments from Past Experiences. IROS (2021)
Weiming Zhi, Lionel Ott, Fabio Ramos
Probabilistic Trajectory Prediction with Structural Constraints. IROS (2021)
Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos
Learning ODEs via Diffeomorphisms for Fast and Robust Integration. CoRR (2021)
Weiming Zhi, Lionel Ott, Fabio Ramos
Probabilistic Trajectory Prediction with Structural Constraints. CoRR (2021)
Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos
Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements. CoRR (2020)
Tin Lai, Weiming Zhi, Fabio Ramos
Occ-Traj120: Occupancy Maps with Associated Trajectories. CoRR (2019)
Weiming Zhi, Lionel Ott, Fabio Ramos
Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction. CoRR (2019)
Weiming Zhi, Lionel Ott, Fabio Ramos
Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction. CoRL (2019)
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) (2019)
Weiming Zhi, Tin Lai, Lionel Ott, Gilad Francis, Fabio Ramos
OCTNet: Trajectory Generation in New Environments from Past Experiences. CoRR (2019)
Weiming Zhi, Lionel Ott, Ransalu Senanayake, Fabio Ramos
Continuous Occupancy Map Fusion with Fast Bayesian Hilbert Maps. ICRA (2019)
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)
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)
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)
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)
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)