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| PROJECT: | Deep learning-based Point Cloud Representation | |||||
| ACRONYM: | Deep-PCR | |||||
| MAIN OBJECTIVE: | The scope of this project is the design, development, implementation and assessment of a DL-based static PC compressed representation targeting both decoding and enhancement consumptions. This will pioneer DL-based solutions that simultaneously accommodate efficient fidelity-to-original PC coding, with compression efficiency improvements over available solutions, and effective enhanced-from-original PC processing using the same compressed domain stream. The expected outcomes are DL-based PC coding and enhancement solutions with the following features: i) efficient PC geometry and color codecs, with and without scalability capabilities, providing the highest fidelity to the original PC for the available rate; and ii) effective PC geometry and color denoising and super-resolution processors, generating enhanced PCs using the same compressed domain stream as the fidelity codec. These outputs should offer the best user experience for multiple application domains, considering different fidelity-to-original requirements. The project will advance the knowledge in the domain and disseminate its achievements with top international conference and journal publications. | |||||
| Reference: | PTDC/EEI-COM/1125/2021 | |||||
| Funding: | FCT | |||||
| Approval Date: | 15-10-2021 | |||||
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| Team: | Fernando Manuel Bernardo Pereira, Nuno Miguel Morais Rodrigues, André Filipe Rodrigues Guarda, Abdelrahman Seleem Mohamed Seleem, Mohammadreza Ghafari | |||||
| Groups: |
Multimedia Signal Processing – Lx Multimedia Signal Processing – Lr |
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| Partners: | IT | |||||
| Local Coordinator: | Fernando Manuel Bernardo Pereira |
This project falls under the following United Nations Strategic Development Goals (SDGs):