Convolutional Neural Network for 3D Point Cloud Quality Assessment with Reference
Author:
Affiliation:
1. Université d’Orléans,Laboratoire PRISME,Orléans,France
2. Université Paris-Saclay,L2S, Centrale Supélec,Gif-sur-Yvette,France
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9733399/9733432/09733565.pdf?arnumber=9733565
Reference30 articles.
1. Quality Evaluation Of Static Point Clouds Encoded Using MPEG Codecs
2. A Color-Based Objective Quality Metric for Point Cloud Contents
3. Towards a Point Cloud Structural Similarity Metric;alexiou;2020 IEEE Intl Conf on Multimedia Expo Workshops (ICMEW),2020
4. Improving Psnr-Based Quality Metrics Performance For Point Cloud Geometry
5. Convolutional Neural Network for Blind Mesh Visual Quality Assessment Using 3D Visual Saliency
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1. PointPCA: point cloud objective quality assessment using PCA-based descriptors;EURASIP Journal on Image and Video Processing;2024-08-09
2. Zoom to Perceive Better: No-Reference Point Cloud Quality Assessment via Exploring Effective Multiscale Feature;IEEE Transactions on Circuits and Systems for Video Technology;2024-07
3. Hallucinated-PQA: No reference point cloud quality assessment via injecting pseudo-reference features;Expert Systems with Applications;2024-06
4. Balancing Representation Abstractions and Local Details Preservation for 3d Point Cloud Quality Assessment;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
5. Point Cloud Quality Assessment Using Multi-Level Features;IEEE Access;2024
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