Dat Thanh Nguyen
Dat Thanh Nguyen, M. Sc.
Research
I am working with point cloud – the data structure used in many applications such as Virtual Reality, Augmented Reality, autonomous vehicles, etc. The main target is to reduce the storage/transmission cost of point cloud and with recent advances in deep learning, I have set a focus on learning-based point cloud compression methods. Different applications require different components/quality levels of the point cloud; therefore, we consider geometry coding as well as attributes coding in both lossless and lossy scenarios. Further information can be found in our Next-Generation Video Communications page.
Publications
2022
Learning-based Lossless Point Cloud Geometry Coding using Sparse Tensors
IEEE International Conference on Image Processing (ICIP) (Bordeaux, France, 16. October 2022 - 19. October 2022)
In: IEEE International Conference on Image Processing
ICIP 2022 2022
URL: https://arxiv.org/abs/2204.05043
BibTeX: Download
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2021
Learning-based lossless compression of 3d point cloud geometry
In: ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021
DOI: 10.1109/ICASSP39728.2021.9414763
URL: https://ieeexplore.ieee.org/abstract/document/9414763
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Lossless Coding of Point Cloud Geometry using a Deep Generative Model
In: IEEE Transactions on Circuits and Systems For Video Technology 31 (2021), p. 4617-4629
ISSN: 1051-8215
DOI: 10.1109/TCSVT.2021.3100279
URL: https://ieeexplore.ieee.org/abstract/document/9496667
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Multiscale deep context modeling for lossless point cloud geometry compression
In: 2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW) 2021
DOI: 10.1109/ICMEW53276.2021.9455990
URL: https://ieeexplore.ieee.org/abstract/document/9455990
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Awards
- : FAU President’s Welcome Award (FAU Welcome Office; Prof. Dr. Joachim Hornegger, President of FAU) – 2021