Pengyuan Wang
Pengyuan Wang
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PhoCaL: A Multi-Modal Dataset for Category-Level Object Pose Estimation with Photometrically Challenging Objects
P Wang, HJ Jung, Y Li, S Shen, RP Srikanth, L Garattoni, S Meier, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstration
P Wang, F Manhardt, L Minciullo, L Garattoni, S Meier, N Navab, B Busam
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021
Polarimetric pose prediction
D Gao, Y Li, P Ruhkamp, I Skobleva, M Wysocki, HJ Jung, P Wang, ...
European Conference on Computer Vision, 735-752, 2022
HouseCat6D--A Large-Scale Multi-Modal Category Level 6D Object Pose Dataset with Household Objects in Realistic Scenarios
HJ Jung, SC Wu, P Ruhkamp, H Schieber, P Wang, G Rizzoli, H Zhao, ...
arXiv preprint arXiv:2212.10428, 2022
CCD-3DR: Consistent Conditioning in Diffusion for Single-Image 3D Reconstruction
Y Di, C Zhang, P Wang, G Zhai, R Zhang, F Manhardt, B Busam, X Ji, ...
arXiv preprint arXiv:2308.07837, 2023
MultiIMU: Fusing Multiple Calibrated IMUs For Enhanced Mixed Reality Tracking
A Jadid, L Rudolph, F Pankratz, K Wu, P Wang, G Klinker
GS-Pose: Category-Level Object Pose Estimation via Geometric and Semantic Correspondence
P Wang, T Ikeda, R Lee, K Nishiwaki
arXiv preprint arXiv:2311.13777, 2023
CroCPS: Addressing Photometric Challenges in Self-Supervised Category-Level 6D Object Poses with Cross-Modal Learning
P Wang, L Garattoni, S Meier, N Navab, B Busam
MultilMU: Fusing Multiple Calibrated IMUs for Enhanced Mixed Reality Tracking: Technischer Bericht
A Jadid, L Rudolph, F Pankratz, K Wu, P Wang, G Klinker
Technische Universität München, Institut für Informatik, 2019
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