Publikationen

In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE Winter Conference on Applications of Computer Vision (WACV-2023), January 3-7, Waikoloa, Hawaii, USA, Pages 1001-1010, IEEE, 2023.

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In: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 1, Pages 1-13, IEEE, 11/2021.

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In: Sensors - Open Access Journal (Sensors), Vol. 20, Pages 1-27, MDPI, 5/2020.

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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). International Conference on Computer Vision and Pattern Recognition (CVPR-2020), June 14-19, The Washington State Convention Center, Washington, USA, IEEE, 2020.

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In: Sensors - Open Access Journal (Sensors), Vol. 19, No. 20, Page 4603, MDPI, 10/2019.

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In: Computers & Graphics (CAG), Vol. 85, Pages 85-91, ELSEVIER, 10/2019.

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In: Sensors - Open Access Journal (Sensors), Vol. 19, Pages 2-15, MDPI, 8/2019.

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In: Proceedings of EuroVR 2018 |. EuroVR (EuroVR-2018), October 22-23, London, United Kingdom, Springer, 11/2018.

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In: Proceedings of 15th EuroVR International Conference |. EuroVR (EuroVR-2018), October 22-23, London, United Kingdom, Springer International Publishing, 11/2018.

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In: Sensors - Open Access Journal (Sensors), Vol. 18, No. 11, Page 3872, MDPI AG, Basel, Switzerland, 11/2018.

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Publikationen

THOR-Net: End-to-End Graformer-Based Realistic Two Hands and Object Reconstruction With Self-Supervision

HandVoxNet++: 3D Hand Shape and Pose Estimation using Voxel-Based Neural Networks

Real-Time Energy Efficient Hand Pose Estimation: A Case Study

HandVoxNet: Deep Voxel-Based Network for 3D Hand Shape and Pose Estimation from a Single Depth Map

Structure from Articulated Motion: Accurate and Stable Monocular 3D Reconstruction without Training Data

Simple and effective deep hand shape and pose regression from a single depth image

WHSP-Net: A Weakly-Supervised Approach for 3D Hand Shape and Pose Recovery from a Single Depth Image

Structure-aware 3D Hand Pose Regression from a Single Depth Image

Fully Automatic Multi-person Human Motion Capture for VR Applications

3DAirSig: A Framework for Enabling In-Air Signatures Using a Multi-Modal Depth Sensor

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