Ming Xu

According to our database, Ming Xu authored at least 21 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Gromov Wasserstein Optimal Transport for Semantic Correspondences.

Francis Snelgar, Stephen Gould, Ming Xu, Liang Zheng, Akshay Asthana

CoRR, February, 2026

2025

DiSA: Diffusion Step Annealing in Autoregressive Image Generation.

Qinyu Zhao, Jaskirat Singh, Ming Xu, Akshay Asthana, Stephen Gould, Liang Zheng

CoRR, May, 2025

Can We Predict Performance of Large Models across Vision-Language Tasks?

Qinyu Zhao, Ming Xu, Kartik Gupta, Akshay Asthana, Liang Zheng, Stephen Gould

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Flexible Geometric Guidance for Probabilistic Human Pose Estimation with Diffusion Models.

Francis Snelgar, Ming Xu, Stephen Gould, Liang Zheng, Akshay Asthana

Proceedings of the 19th IEEE International Conference on Automatic Face and Gesture Recognition, 2025

Context-Dependent Anomaly Action Recognition.

Nutthadech Banditakkarakul, Ming Xu, Bo Chen, Akshay Asthana, Liang Zheng, Stephen Gould

Proceedings of the 19th IEEE International Conference on Automatic Face and Gesture Recognition, 2025

2024

Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection.

Qinyu Zhao, Ming Xu, Kartik Gupta, Akshay Asthana, Liang Zheng, Stephen Gould

Proceedings of the Twelfth International Conference on Learning Representations, 2024

The First to Know: How Token Distributions Reveal Hidden Knowledge in Large Vision-Language Models?

Qinyu Zhao, Ming Xu, Kartik Gupta, Akshay Asthana, Liang Zheng, Stephen Gould

Proceedings of the Computer Vision - ECCV 2024, 2024

VLAD-BuFF: Burst-Aware Fast Feature Aggregation for Visual Place Recognition.

Ahmad Khaliq, Ming Xu, Stephen Hausler, Michael Milford, Sourav Garg

Proceedings of the Computer Vision - ECCV 2024, 2024

Temporally Consistent Unbalanced Optimal Transport for Unsupervised Action Segmentation.

Ming Xu, Stephen Gould

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Deep Declarative Dynamic Time Warping for End-to-End Learning of Alignment Paths.

Ming Xu, Sourav Garg, Michael Milford, Stephen Gould

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Improving Road Segmentation in Challenging Domains Using Similar Place Priors.

Connor Malone, Sourav Garg, Ming Xu, Thierry Peynot, Michael Milford

IEEE Robotics Autom. Lett., 2022

Improving Worst Case Visual Localization Coverage via Place-Specific Sub-Selection in Multi-Camera Systems.

Stephen Hausler, Ming Xu, Sourav Garg, Punarjay Chakravarty, Shubham Shrivastava, Ankit Vora, Michael Milford

IEEE Robotics Autom. Lett., 2022

Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics.

Krishan Rana, Ming Xu, Brendan Tidd, Michael Milford, Niko Sünderhauf

Proceedings of the Conference on Robot Learning, 2022

2021

Probabilistic Appearance-Invariant Topometric Localization With New Place Awareness.

Ming Xu, Tobias Fischer, Niko Sünderhauf, Michael Milford

IEEE Robotics Autom. Lett., October, 2021

Corrections to "Probabilistic Visual Place Recognition for Hierarchical Localization".

Ming Xu, Niko Sünderhauf, Michael Milford

IEEE Robotics Autom. Lett., 2021

Probabilistic Visual Place Recognition for Hierarchical Localization.

Ming Xu, Niko Sünderhauf, Michael Milford

IEEE Robotics Autom. Lett., 2021

Unsupervised Selection of Optimal Operating Parameters for Visual Place Recognition Algorithms Using Gaussian Mixture Models.

James Mount, Ming Xu, Les Dawes, Michael Milford

IEEE Robotics Autom. Lett., 2021

Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition.

Stephen Hausler, Sourav Garg, Ming Xu, Michael Milford, Tobias Fischer

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2019

Hierarchical Encoding of Sequential Data With Compact and Sub-Linear Storage Cost.

Huu Le, Ming Xu, Tuan Hoang, Michael Milford

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Variance reduction properties of the reparameterization trick.

Ming Xu, Matias Quiroz, Robert Kohn, Scott A. Sisson

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

On some variance reduction properties of the reparameterization trick.

Ming Xu, Matias Quiroz, Robert Kohn, Scott A. Sisson

CoRR, 2018