M. Zeeshan Zia

Orcid: 0000-0001-8221-2637

Affiliations:
  • Microsoft, Redmond, WA, USA
  • Imperial College London, Robot Vision Laboratory, UK (former)
  • ETH Zurich, Photogrammetry & Remote Sensing Lab, Switzerland (former)


According to our database1, M. Zeeshan Zia authored at least 29 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Permutation-Aware Activity Segmentation via Unsupervised Frame-to-Segment Alignment.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Action Segmentation Using 2D Skeleton Heatmaps and Multi-Modality Fusion.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Learning by Aligning 2D Skeleton Sequences and Multi-modality Fusion.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
Domain-Specific Priors and Meta Learning for Few-Shot First-Person Action Recognition.
IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

Action Segmentation Using 2D Skeleton Heatmaps.
CoRR, 2023

Learning by Aligning 2D Skeleton Sequences in Time.
CoRR, 2023

Permutation-Aware Action Segmentation via Unsupervised Frame-to-Segment Alignment.
CoRR, 2023

2022
AI-mediated Job Status Tracking in AR as a No-Code service.
Proceedings of the 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), 2022

Timestamp-Supervised Action Segmentation with Graph Convolutional Networks.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Unsupervised Action Segmentation by Joint Representation Learning and Online Clustering.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Unsupervised Activity Segmentation by Joint Representation Learning and Online Clustering.
CoRR, 2021

Learning by Aligning Videos in Time.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Towards Anomaly Detection in Dashcam Videos.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

2019
Deep Supervision with Intermediate Concepts.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Domain-Specific Priors and Meta Learning for Low-shot First-Person Action Recognition.
CoRR, 2019

2018
Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences.
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
Deep Supervision with Shape Concepts for Occlusion-Aware 3D Object Parsing.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Comparative design space exploration of dense and semi-dense SLAM.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Monocular reconstruction of vehicles: Combining SLAM with shape priors.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Integrating Algorithmic Parameters into Benchmarking and Design Space Exploration in 3D Scene Understanding.
Proceedings of the 2016 International Conference on Parallel Architectures and Compilation, 2016

2015
Towards Scene Understanding with Detailed 3D Object Representations.
Int. J. Comput. Vis., 2015

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014
High-Resolution 3D Layout from a Single View.
PhD thesis, 2014

Are Cars Just 3D Boxes? Jointly Estimating the 3D Shape of Multiple Objects.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Detailed 3D Representations for Object Recognition and Modeling.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

Explicit Occlusion Modeling for 3D Object Class Representations.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2011
Revisiting 3D geometric models for accurate object shape and pose.
Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

2009
3D model selection from an internet database for robotic vision.
Proceedings of the 2009 IEEE International Conference on Robotics and Automation, 2009

Acquisition of a dense 3D model database for robotic vision.
Proceedings of the 14th International Conference on Advanced Robotics, 2009


  Loading...