Point Cloud Quality Assessment Using Cross-correlation of Deep Features-Reference-Cited by-同舟云学术

Point Cloud Quality Assessment Using Cross-correlation of Deep Features

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2nd Workshop on Quality of Experience in Visual Multimedia Applications
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Author:

Tliba Marouane¹,Chetouani Aladine¹,Valenzise Giuseppe²,Dufaux Frederic²

Affiliation:

1. University of Orleans, PRISME, Orleans, France

2. University of Paris-Saclay,CNRS, CentraleSupélec, Paris, France

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3552469.3555710

Reference27 articles.

1. E. Alexiou and T. Ebrahimi. 2018. Point Cloud Quality Assessment Metric based on Angular Similarity. In IEEE ICME-W. E. Alexiou and T. Ebrahimi. 2018. Point Cloud Quality Assessment Metric based on Angular Similarity. In IEEE ICME-W.

2. Salima Bourbia Ayoub Karine Aladine Chetouani and Mohammed El Hassouni. 2022. Blind Projection-based 3D Point Cloud Quality Assessment Method using a Convolutional Neural Network Giovanni Maria Farinella Petia Radeva and Kadi Bouatouch (Eds.). 518--525. https://doi.org/10.5220/0010872700003124 10.5220/0010872700003124

3. Salima Bourbia Ayoub Karine Aladine Chetouani and Mohammed El Hassouni. 2022. Blind Projection-based 3D Point Cloud Quality Assessment Method using a Convolutional Neural Network Giovanni Maria Farinella Petia Radeva and Kadi Bouatouch (Eds.). 518--525. https://doi.org/10.5220/0010872700003124

4. Compression of Sparse and Dense Dynamic Point Clouds—Methods and Standards

5. Xinlei Chen and Kaiming He . 2021 . Exploring Simple Siamese Representation Learning. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021), 15745--15753. Xinlei Chen and Kaiming He. 2021. Exploring Simple Siamese Representation Learning. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021), 15745--15753.

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