Mahdi Rad - Concepedia

Author

Mahdi Rad

Graz University of Technology ORCID

Also Known As

, M. Torabi Rad, Mahdi Rad, Mahdi Torabi Rad, RAD, Mahdi, Rad, M. Torabi, Rad, Mahdi, Rad, Mahdi Torabi

Publications

Citations

H-Index

Concepts

All Affiliations

Graz University of Technology Laboratoire d'Informatique Gaspard-Monge École Polytechnique Fédérale de Lausanne Université Gustave Eiffel Centre National de la Recherche Scientifique

About

Mahdi Rad is an author at Graz University of Technology specializing in engineering, computer vision, and machine vision.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	9	9	360
2	Natural Sciences	3	3	164
3	Materials Science	3	3	84
4	Dance	1	1	23
5	Kinesiology	1	1	12

Mahdi Rad

Publications

1.5K

Citations

H-Index

Page 1

	Year	Citations
BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth Mahdi Rad, Vincent Lepetit	2017	852
Keypoint Transformer: Solving Joint Identification in Challenging Hands and Object Interactions for Accurate 3D Pose Estimation Shreyas Hampali, Sayan Sarkar, Mahdi Rad, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)	2022	149
Feature Mapping for Learning Fast and Accurate 3D Pose Inference from Synthetic Images Mahdi Rad, Markus Oberweger, Vincent Lepetit HAL (Le Centre pour la Communication Scientifique Directe)	2018	137
Robust 3D Object Tracking from Monocular Images Using Stable Parts Alberto Crivellaro, Mahdi Rad, Yannick Verdié, IEEE Transactions on Pattern Analysis and Machine Intelligence EngineeringObject Parts3D Pose EstimationMulti-view Geometry3D Computer Vision	2017	78
A Novel Representation of Parts for Accurate 3D Object Detection and Tracking in Monocular Images Alberto Crivellaro, Mahdi Rad, Yannick Verdié, Engineering3D Pose EstimationComputer-aided DesignKnown Object3D Computer Vision	2015	74
BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth Mahdi Rad, Vincent Lepetit arXiv (Cornell University) Using DepthMachine LearningEngineeringPartial Occlusion MethodChallenging Objects	2017	71
Rayleigh Number Criterion for Formation of A-Segregates in Steel Castings and Ingots Mahdi Rad, Petr Kotas, C. Beckermann Metallurgical and Materials Transactions A Materials ScienceRayleigh Number CriterionEngineeringMechanical EngineeringMetallurgical Process	2013	36
Theory-training deep neural networks for an alloy solidification benchmark problem Mahdi Rad, Alexandre Viardin, Georg J. Schmitz, Computational Materials Science Materials ScienceArtificial IntelligenceModel OptimizationEngineeringMachine Learning	2020	34
HoloAssist: an Egocentric Human Interaction Dataset for Interactive AI Assistants in the Real World Xin Wang, Taein Kwon, Mahdi Rad,	2023	34
HOnnotate: A Method for 3D Annotation of Hand and Object Poses Shreyas Hampali, Mahdi Rad, Markus Oberweger, EngineeringMachine LearningHuman Pose Estimation3D Pose Estimation3D Computer Vision	2020	23

Page 1