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Point Cloud Quality Assessment: Dataset Construction and Learning-based No-reference Metric

https://doi.org/10.1145/3550274
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/11263.1573-1405openalex-snapshot
International Journal of Computer Vision
inferredcites →https://doi.org/10.1007/s11432-019-2757-1openalex-snapshot
Perceptual image quality assessment: a survey
inferredcites →https://doi.org/10.1016/j.cviu.2014.04.011openalex-snapshot
SHOT: Unique signatures of histograms for surface and texture description
inferredcites →https://doi.org/10.1016/j.image.2014.10.009openalex-snapshot
Image database TID2013: Peculiarities, results and perspectives
inferredcites →https://doi.org/10.1016/j.sigpro.2015.08.012openalex-snapshot
Biologically inspired image quality assessment
inferredcites →https://doi.org/10.1109/34.765655openalex-snapshot
Using spin images for efficient object recognition in cluttered 3D scenes
inferredcites →https://doi.org/10.1109/access.2022.3198995openalex-snapshot
Joint Geometry and Color Projection-Based Point Cloud Quality Metric
inferredcites →https://doi.org/10.1109/cvpr.1993openalex-snapshot
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
inferredcites →https://doi.org/10.1109/cvpr.2018.00961openalex-snapshot
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
inferredcites →https://doi.org/10.1109/iccv.1995.466933openalex-snapshot
Proceedings of IEEE International Conference on Computer Vision
inferredcites →https://doi.org/10.1109/icme.2002openalex-snapshot
Proceedings. IEEE International Conference on Multimedia and Expo
inferredcites →https://doi.org/10.1109/iros.1992openalex-snapshot
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems
inferredcites →https://doi.org/10.1109/iscas.2003.1206140openalex-snapshot
Proceedings Of The 2003 IEEE International Symposium On Circuits And systems
inferredcites →https://doi.org/10.1109/iscas.2019.8702664openalex-snapshot
MC360IQA: The Multi-Channel CNN for Blind 360-Degree Image Quality Assessment
inferredcites →https://doi.org/10.1109/jstsp.2019.2955024openalex-snapshot
MC360IQA: A Multi-channel CNN for Blind 360-Degree Image Quality Assessment
inferredcites →https://doi.org/10.1109/lsp.2020.3024065openalex-snapshot
A Reduced Reference Metric for Visual Quality Evaluation of Point Cloud Contents
inferredcites →https://doi.org/10.1109/robot.1985openalex-snapshot
Proceedings. 1985 IEEE International Conference on Robotics and Automation
inferredcites →https://doi.org/10.1109/tcsvt.2021.3100282openalex-snapshot
PQA-Net: Deep No Reference Point Cloud Quality Assessment via Multi-View Projection
inferredcites →https://doi.org/10.1109/tcsvt.2022.3186894openalex-snapshot
No-Reference Quality Assessment for 3D Colored Point Cloud and Mesh Models
inferredcites →https://doi.org/10.1109/tim.2020.2984928openalex-snapshot
Blind Image Quality Measurement by Exploiting High-Order Statistics With Deep Dictionary Encoding Network
inferredcites →https://doi.org/10.1109/tim.2020.3005111openalex-snapshot
A Full-Reference Stereoscopic Image Quality Measurement Via Hierarchical Deep Feature Degradation Fusion
inferredcites →https://doi.org/10.1109/tip.2003.819861openalex-snapshot
Image quality assessment: from error visibility to structural similarity
inferredcites →https://doi.org/10.1109/tip.2005.859378openalex-snapshot
Image information and visual quality
inferredcites →https://doi.org/10.1109/tip.2013.2293423openalex-snapshot
Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index
inferredcites →https://doi.org/10.1109/tip.2016.2631888openalex-snapshot
Waterloo Exploration Database: New Challenges for Image Quality Assessment Models
inferredcites →https://doi.org/10.1109/tip.2017.2735192openalex-snapshot
Unified Blind Quality Assessment of Compressed Natural, Graphic, and Screen Content Images
inferredcites →https://doi.org/10.1109/tip.2020.2966081openalex-snapshot
A Metric for Light Field Reconstruction, Compression, and Display Quality Evaluation
inferredcites →https://doi.org/10.1109/tip.2020.2988148openalex-snapshot
Study of Subjective and Objective Quality Assessment of Audio-Visual Signals
inferredcites →https://doi.org/10.1109/tip.2020.3002478openalex-snapshot
End-to-End Blind Image Quality Prediction With Cascaded Deep Neural Network
inferredcites →https://doi.org/10.1109/tip.2021.3096060openalex-snapshot
Reduced Reference Perceptual Quality Model With Application to Rate Control for Video-Based Point Cloud Compression
inferredcites →https://doi.org/10.1109/tits.2018.2868771openalex-snapshot
Objective Quality Evaluation of Dehazed Images
inferredcites →https://doi.org/10.1109/tmm.2017.2763321openalex-snapshot
Optimizing Multistage Discriminative Dictionaries for Blind Image Quality Assessment
inferredcites →https://doi.org/10.1109/tmm.2019.2902097openalex-snapshot
Quality Evaluation of Image Dehazing Methods Using Synthetic Hazy Images
inferredcites →https://doi.org/10.1109/tmm.2020.3033117openalex-snapshot
Predicting the Perceptual Quality of Point Cloud: A 3D-to-2D Projection-Based Exploration
inferredcites →https://doi.org/10.1109/tmm.2020.3037481openalex-snapshot
Point Cloud Rendering After Coding: Impacts on Subjective and Objective Quality
inferredcites →https://doi.org/10.1109/tpami.2020.3047083openalex-snapshot
Inferring Point Cloud Quality via Graph Similarity
inferredcites →https://doi.org/10.1109/tvcg.2022.3167151openalex-snapshot
Perceptual Quality Assessment of Colored 3D Point Clouds
inferredcites →https://doi.org/10.1111/1467-8659.00236openalex-snapshot
Metro: Measuring Error on Simplified Surfaces
inferredcites →https://doi.org/10.1117/12.2322741openalex-snapshot
A novel methodology for quality assessment of voxelized point clouds
inferredcites →https://doi.org/10.1145/1877808.1877821openalex-snapshot
Unique shape context for 3d data description
inferredcites →https://doi.org/10.1145/3176649openalex-snapshot
Deformation-Based 3D Facial Expression Representation
inferredcites →https://doi.org/10.1145/3282833openalex-snapshot
Expression Robust 3D Facial Landmarking via Progressive Coarse-to-Fine Tuning
inferredcites →https://doi.org/10.1145/3470970openalex-snapshot
Screen Content Quality Assessment: Overview, Benchmark, and Beyond
inferredcites →https://doi.org/10.5121/sipij.2015.6206openalex-snapshot
A Review Paper : Noise Models in Digital Image Processing

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/aisy.202500504openalex-snapshot
BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models
inferred← citeshttps://doi.org/10.1002/rob.22303openalex-snapshot
RoboBoat: A robotic boat for 3D mapping of partially flooded underground sites
inferred← citeshttps://doi.org/10.1007/978-3-031-82427-2_15openalex-snapshot
Visual Point Cloud Quality Assessment Using Graph Attention Network
inferred← citeshttps://doi.org/10.1007/s00530-025-01887-2openalex-snapshot
Mpv-pcqa: multimodal no-reference point cloud quality assessment via point cloud and captured dynamic video
inferred← citeshttps://doi.org/10.1007/s00530-025-02167-9openalex-snapshot
DPR-Net: dual-branch probabilistic regression for no-reference point cloud quality assessment
inferred← citeshttps://doi.org/10.1007/s11760-026-05289-3openalex-snapshot
Autoencoder-based 3D Model Pretraining for No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1016/j.cag.2025.104176openalex-snapshot
No-reference geometry quality assessment for colorless point clouds via list-wise rank learning
inferred← citeshttps://doi.org/10.1016/j.displa.2023.102540openalex-snapshot
A no-reference quality assessment metric for dynamic 3D digital human
inferred← citeshttps://doi.org/10.1016/j.displa.2025.103137openalex-snapshot
3DRMF: No-reference 3D point cloud quality assessment with Rotation Mamba Fusion
inferred← citeshttps://doi.org/10.1016/j.displa.2026.103443openalex-snapshot
MDM-PCQA: No-reference point cloud quality assessment method via multi-distortion modeling
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.122953openalex-snapshot
Hallucinated-PQA: No reference point cloud quality assessment via injecting pseudo-reference features
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.125039openalex-snapshot
Wave-PCT: Wavelet point cloud transformer for point cloud quality assessment
inferred← citeshttps://doi.org/10.1016/j.image.2024.117156openalex-snapshot
Quality evaluation of point cloud compression techniques
inferred← citeshttps://doi.org/10.1016/j.image.2024.117239openalex-snapshot
Full reference point cloud quality assessment using support vector regression
inferred← citeshttps://doi.org/10.1016/j.image.2025.117262openalex-snapshot
PointPCA+: A full-reference Point Cloud Quality Assessment metric with PCA-based features
inferred← citeshttps://doi.org/10.1016/j.image.2025.117371openalex-snapshot
CT-PCQA: A Convolutional Neural Network and Transformer combined Method for Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1016/j.iswa.2025.200570openalex-snapshot
NSS-MDL: Natural Scene Statistics-guided multi-task deep learning for no-reference point cloud quality assessment
inferred← citeshttps://doi.org/10.1016/j.rcim.2024.102863openalex-snapshot
A robust assessment method of point cloud quality for enhancing 3D robotic scanning
inferred← citeshttps://doi.org/10.1080/01431161.2026.2686303openalex-snapshot
Lightweight quality enhancement of ALS point clouds for tree species classification performance
inferred← citeshttps://doi.org/10.1109/access.2023.3247191openalex-snapshot
No-Reference 3D Point Cloud Quality Assessment Using Multi-View Projection and Deep Convolutional Neural Network
inferred← citeshttps://doi.org/10.1109/access.2023.3321912openalex-snapshot
Key Indicators to Assess the Performance of LiDAR-Based Perception Algorithms: A Literature Review
inferred← citeshttps://doi.org/10.1109/access.2023.3332141openalex-snapshot
CloudUP—Upsampling Vibrant Color Point Clouds Using Multi-Scale Spatial Attention
inferred← citeshttps://doi.org/10.1109/access.2024.3383536openalex-snapshot
Point Cloud Quality Assessment Using Multi-Level Features
inferred← citeshttps://doi.org/10.1109/access.2024.3521093openalex-snapshot
Point Cloud Quality Assessment Based on Cross-Modal De-Redundancy
inferred← citeshttps://doi.org/10.1109/access.2025.3561895openalex-snapshot
Performance Analysis of Deep Learning-Based Lossy Point Cloud Geometry Compression Coding Solutions
inferred← citeshttps://doi.org/10.1109/access.2025.3567190openalex-snapshot
NEUF: Learning Point Cloud Quality by Non-Euclidean Fast Filtering
inferred← citeshttps://doi.org/10.1109/access.2025.3649889openalex-snapshot
Novel Point Cloud Distance Metric With Adjustable Error Sensitivity and Shape Compensation
inferred← citeshttps://doi.org/10.1109/access.2026.3660979openalex-snapshot
SAGANet: Structure-Aware Geometric Anisotropy Network for Point Cloud Compression and Upsampling
inferred← citeshttps://doi.org/10.1109/access.2026.3698729openalex-snapshot
Objective Quality Evaluation of Point Clouds: Quality Features and Fusion Metrics
inferred← citeshttps://doi.org/10.1109/bmsb65076.2025.11165660openalex-snapshot
Estimating Quality of Experience in Multicast Point Cloud Streaming over 5G Networks
inferred← citeshttps://doi.org/10.1109/cvpr52733.2024.02451openalex-snapshot
Contrastive Pre-Training with Multi-View Fusion for No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/euvip66349.2025.11238901openalex-snapshot
A No-Reference Point Cloud Quality Assessment Using Graph Attention Networks and Keypoint Resampling
inferred← citeshttps://doi.org/10.1109/ic2sdt62152.2024.10696729openalex-snapshot
Quality Assessment for 3D Coloured Point Clouds in Autonomous Vehicles
inferred← citeshttps://doi.org/10.1109/icaace65325.2025.11019072openalex-snapshot
Research on the Influence of Point Cloud Geometric Features on Compression Algorithm
inferred← citeshttps://doi.org/10.1109/icassp48485.2024.10445736openalex-snapshot
MFT-PCQA: Multi-Modal Fusion Transformer for No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/icassp48485.2024.10448511openalex-snapshot
Rating-Augmented No-Reference Point Cloud Quality Assessment Using Multi-Task Learning
inferred← citeshttps://doi.org/10.1109/icassp49357.2023.10095347openalex-snapshot
Perceptual Quality Assessment for Digital Human Heads
inferred← citeshttps://doi.org/10.1109/icassp49357.2023.10096048openalex-snapshot
Surface-Sampling Based Objective Quality Assessment Metrics for Meshes
inferred← citeshttps://doi.org/10.1109/icassp49357.2023.10096258openalex-snapshot
ψ-Net: Point Structural Information Network for No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/icassp49660.2025.10888315openalex-snapshot
No-Reference Point Cloud Quality Assessment Based on Graph Signal Variation
inferred← citeshttps://doi.org/10.1109/icassp49660.2025.10889736openalex-snapshot
Full-Reference Point Cloud Quality Assessment with Multimodal Large Language Models
inferred← citeshttps://doi.org/10.1109/icassp49660.2025.10889921openalex-snapshot
3DGCQA: A Quality Assessment Database for 3D AI-Generated Contents
inferred← citeshttps://doi.org/10.1109/icip49359.2023.10221964openalex-snapshot
A No-Reference Quality Assessment Method for Digital Human Head
inferred← citeshttps://doi.org/10.1109/icip55913.2025.11084354openalex-snapshot
PIT-QMM: A Large Multimodal Model for No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/icip55913.2025.11084493openalex-snapshot
No-Reference Textured Mesh Quality Assessment Using Graph-Based Features
inferred← citeshttps://doi.org/10.1109/icipc59416.2023.10328338openalex-snapshot
PointPCA+: Extending PointPCA Objective Quality Assessment Metric
inferred← citeshttps://doi.org/10.1109/icipc59416.2023.10328342openalex-snapshot
BPQA: A Blind Point Cloud Quality Assessment Method
inferred← citeshttps://doi.org/10.1109/icme55011.2023.00423openalex-snapshot
EEP-3DQA: Efficient and Effective Projection-Based 3D Model Quality Assessment
inferred← citeshttps://doi.org/10.1109/icme55011.2023.00429openalex-snapshot
DDH-QA: A Dynamic Digital Humans Quality Assessment Database
inferred← citeshttps://doi.org/10.1109/icme59968.2025.11209854openalex-snapshot
VIP-PCQA: A Multi-Modal Framework for No-reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/icme59968.2025.11210051openalex-snapshot
DPCD: A Quality Assessment Database for Dynamic Point Clouds
inferred← citeshttps://doi.org/10.1109/icmlc66258.2025.11280131openalex-snapshot
MMFN-PCQA: A Novel Muti-Modal Fusion Network for no-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/icmlca66850.2025.11336814openalex-snapshot
No-Reference Point Cloud Quality Assessment Based on Gradient Saliency
inferred← citeshttps://doi.org/10.1109/ipta66025.2025.11222053openalex-snapshot
Knowledge Distillation Between 2D and 3D Vision Transformers for Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/iv66570.2026.11623873openalex-snapshot
Data Readiness Levels for Automated Driving
inferred← citeshttps://doi.org/10.1109/lsp.2024.3452556openalex-snapshot
LLM-Guided Cross-Modal Point Cloud Quality Assessment: A Graph Learning Approach
inferred← citeshttps://doi.org/10.1109/lsp.2026.3718778openalex-snapshot
Topological Feature Fusion for Multi-Channel No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/mmsp55362.2022.9949359openalex-snapshot
A No-reference Quality Assessment Metric for Point Cloud Based on Captured Video Sequences
inferred← citeshttps://doi.org/10.1109/qomex61742.2024.10598277openalex-snapshot
Assessing objective quality metrics for JPEG and MPEG point cloud coding
inferred← citeshttps://doi.org/10.1109/qomex65720.2025.11219947openalex-snapshot
Local Structure Matters: A Graph-Based Approach to Point Cloud Perceptual Quality Assessment
inferred← citeshttps://doi.org/10.1109/qomex65720.2025.11219985openalex-snapshot
MVAW-PCQA: A No-reference Point Cloud Quality Assessment via Multi-View Adaptive Weighting
inferred← citeshttps://doi.org/10.1109/qomex69967.2026.11617375openalex-snapshot
Prompt2Point: A Reference-Based Dataset for Dynamic Volumetric Quality Assessment
inferred← citeshttps://doi.org/10.1109/qomex69967.2026.11618331openalex-snapshot
M3DGCQA: A Quality Assessment Dataset for Multi-Object 3D Generated Contents
inferred← citeshttps://doi.org/10.1109/qomex69967.2026.11618383openalex-snapshot
DAL-PCQA: Enabling Distortion-Level and Language-Driven Reasoning for Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/qomex69967.2026.11618387openalex-snapshot
Not All Views Matter: A View-Selective Approach to Point Cloud Perceptual Quality Assessment
inferred← citeshttps://doi.org/10.1109/sitis61268.2023.00070openalex-snapshot
Point Cloud Quality Assessment using 1D VGG16 based Transfer Learning Model
inferred← citeshttps://doi.org/10.1109/smc54092.2024.10831641openalex-snapshot
A No Reference Deep Quality Assessment Index for 3D Colored Meshes
inferred← citeshttps://doi.org/10.1109/tbc.2024.3482173openalex-snapshot
No-Reference Point Cloud Quality Assessment Through Structure Sampling and Clustering Based on Graph
inferred← citeshttps://doi.org/10.1109/tbc.2025.3541862openalex-snapshot
Once-Training-All-Fine: No-Reference Point Cloud Quality Assessment via Domain-Relevance Degradation Description
inferred← citeshttps://doi.org/10.1109/tbc.2025.3553305openalex-snapshot
Low-Complexity Patch-Based No-Reference Point Cloud Quality Metric Exploiting Weighted Structure and Texture Features
inferred← citeshttps://doi.org/10.1109/tbc.2025.3597096openalex-snapshot
COPP-Net: No-Reference Point Cloud Quality Assessment via Weighted Patch Quality Prediction
inferred← citeshttps://doi.org/10.1109/tbc.2026.3666667openalex-snapshot
UPDA: Unsupervised Progressive Domain Adaptation for No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tbc.2026.3689330openalex-snapshot
DI-PCQA: Domain-Invariant Learning Framework for No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tbc.2026.3696545openalex-snapshot
Advancing No-Reference Point Cloud Quality Assessment via Leveraging Prior Knowledge From Ranking Learning
inferred← citeshttps://doi.org/10.1109/tcsvt.2024.3350180openalex-snapshot
Plain-PCQA: No-Reference Point Cloud Quality Assessment by Analysis of Plain Visual and Geometrical Components
inferred← citeshttps://doi.org/10.1109/tcsvt.2024.3362369openalex-snapshot
Zoom to Perceive Better: No-Reference Point Cloud Quality Assessment via Exploring Effective Multiscale Feature
inferred← citeshttps://doi.org/10.1109/tcsvt.2024.3410052openalex-snapshot
Dynamic Hypergraph Convolutional Network for No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tcsvt.2024.3510733openalex-snapshot
Asynchronous Feedback Network for Perceptual Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tcsvt.2025.3541445openalex-snapshot
The Worse the Better: Content-Aware Viewpoint Generation Network for Projection-Related Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tcsvt.2025.3588299openalex-snapshot
DQP-PCQA: Deep Quantization Parameters Bring New Insight to Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tcsvt.2025.3624798openalex-snapshot
Cellular Aggregation Graph Convolutional Network for Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tcsvt.2025.3633154openalex-snapshot
From Images to Point Clouds: An Efficient Solution for Cross-Media Blind Quality Assessment Without Annotated Training
inferred← citeshttps://doi.org/10.1109/telfor56187.2022.9983762openalex-snapshot
No-reference local image quality evaluation
inferred← citeshttps://doi.org/10.1109/tim.2023.3322475openalex-snapshot
Applying Collaborative Adversarial Learning to Blind Point Cloud Quality Measurement
inferred← citeshttps://doi.org/10.1109/tim.2025.3529543openalex-snapshot
Information Exploration of Projected Views for Point Cloud Quality Measurement
inferred← citeshttps://doi.org/10.1109/tim.2025.3541782openalex-snapshot
CMDC-PCQA: No-Reference Point Cloud Quality Assessment via a Cross-Modal Deep-Coupling Framework
inferred← citeshttps://doi.org/10.1109/tim.2025.3565097openalex-snapshot
Evaluating Visual Quality of Autostereoscopic Displays Using an Interactive Perception Network
inferred← citeshttps://doi.org/10.1109/tim.2026.3667351openalex-snapshot
EGMS-PCQM: Entropy-Guided Multiscale Sampling-Based Dual-Net for No-Reference Point Cloud Quality Measurement
inferred← citeshttps://doi.org/10.1109/tim.2026.3680192openalex-snapshot
Just Noticeable Difference Measurement for Point Cloud Compression: A Benchmark Dataset and Prediction Network
inferred← citeshttps://doi.org/10.1109/tip.2022.3214077openalex-snapshot
Graph-Based Depth Denoising & Dequantization for Point Cloud Enhancement
inferred← citeshttps://doi.org/10.1109/tip.2023.3253252openalex-snapshot
Bitstream-Based Perceptual Quality Assessment of Compressed 3D Point Clouds
inferred← citeshttps://doi.org/10.1109/tip.2024.3468881openalex-snapshot
Subjective and Objective Quality Assessment of Rendered Human Avatar Videos in Virtual Reality
inferred← citeshttps://doi.org/10.1109/tip.2024.3468893openalex-snapshot
Perception-Guided Quality Metric of 3D Point Clouds Using Hybrid Strategy
inferred← citeshttps://doi.org/10.1109/tip.2025.3539465openalex-snapshot
Energy-Adaptive Bitstream-Layer Model for Perceptual Quality Assessment of V-PCC Encoded 3D Point Clouds
inferred← citeshttps://doi.org/10.1109/tip.2025.3570597openalex-snapshot
Advancing Zero-Shot Digital Human Quality Assessment Through Text-Prompted Evaluation
inferred← citeshttps://doi.org/10.1109/tip.2025.3607630openalex-snapshot
Structure-Aware Generative Point Cloud Compression for Visual Perception
inferred← citeshttps://doi.org/10.1109/tip.2025.3640023openalex-snapshot
DA-Net: A Double Alignment Multimodal Learning Network for Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tip.2026.3705200openalex-snapshot
Multi-Dimensional Quality Assessment for Single-Image-to-3D Contents: Dataset and Model
inferred← citeshttps://doi.org/10.1109/tmm.2023.3340894openalex-snapshot
Evaluating Point Cloud From Moving Camera Videos: A No-Reference Metric
inferred← citeshttps://doi.org/10.1109/tmm.2023.3347638openalex-snapshot
Support Vector Regression-Based Reduced- Reference Perceptual Quality Model for Compressed Point Clouds
inferred← citeshttps://doi.org/10.1109/tmm.2024.3407698openalex-snapshot
3DTA: No-Reference 3D Point Cloud Quality Assessment With Twin Attention
inferred← citeshttps://doi.org/10.1109/tmm.2024.3443634openalex-snapshot
Colored Point Cloud Quality Assessment Using Complementary Features in 3D and 2D Spaces
inferred← citeshttps://doi.org/10.1109/tmm.2024.3521845openalex-snapshot
No-Reference Point Cloud Quality Assessment via Graph Convolutional Network
inferred← citeshttps://doi.org/10.1109/tmm.2025.3604905openalex-snapshot
Multi-Dimensional Quality Assessment for Text-to-3D Assets: Dataset and Model
inferred← citeshttps://doi.org/10.1109/tmm.2025.3613114openalex-snapshot
Local and Global Structure-Guided No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tmm.2025.3645602openalex-snapshot
RegR-PCQA: Deep Learning Based Colored Point Cloud Quality Assessment Using 3D-to-2D Regularized Representation
inferred← citeshttps://doi.org/10.1109/tmm.2026.3676159openalex-snapshot
Dynamic Alignment Learning With Multi-Level Perceptual Stimuli for No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tpami.2022.3213831openalex-snapshot
MPED: Quantifying Point Cloud Distortion Based on Multiscale Potential Energy Discrepancy
inferred← citeshttps://doi.org/10.1109/tvcg.2023.3282802openalex-snapshot
GPA-Net:No-Reference Point Cloud Quality Assessment With Multi-Task Graph Convolutional Network
inferred← citeshttps://doi.org/10.1109/tvcg.2023.3320236openalex-snapshot
HEADSET: Human Emotion Awareness under Partial Occlusions Multimodal DataSET
inferred← citeshttps://doi.org/10.1109/tvcg.2024.3443911openalex-snapshot
No-Reference Bitstream-Based Perceptual Quality Assessment of Octree-Lifting Encoded 3D Point Clouds
inferred← citeshttps://doi.org/10.1109/tvcg.2025.3532651openalex-snapshot
Progressive Knowledge Transfer Network Based on Human Visual Perception Mechanism for No-Reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1109/tvcg.2025.3582309openalex-snapshot
Revisit Point Cloud Quality Assessment: Current Advances and a Multiscale-Inspired Approach
inferred← citeshttps://doi.org/10.1109/tvcg.2025.3629111openalex-snapshot
Perceptual Quality Assessment of Trisoup-Lifting Encoded 3D Point Clouds
inferred← citeshttps://doi.org/10.1109/vcip56404.2022.10008813openalex-snapshot
Reduced Reference Quality Assessment for Point Cloud Compression
inferred← citeshttps://doi.org/10.1109/vcip63160.2024.10849833openalex-snapshot
No-Reference Point Cloud Quality Assessment with Adaptive Keyframe Selection
inferred← citeshttps://doi.org/10.1109/vcip63160.2024.10849927openalex-snapshot
Differentiable Low-computation Global Correlation Loss for Monotonicity Evaluation in Quality Assessment
inferred← citeshttps://doi.org/10.1109/vcip67698.2025.11396893openalex-snapshot
Learning-Based Objective Perceptual Quality Models Across Interactive and Immersive Media
inferred← citeshttps://doi.org/10.1145/3587819.3592543openalex-snapshot
VOLVQAD: An MPEG V-PCC Volumetric Video Quality Assessment Dataset
inferred← citeshttps://doi.org/10.1145/3624983openalex-snapshot
Underwater Image Quality Assessment from Synthetic to Real-world: Dataset and Objective Method
inferred← citeshttps://doi.org/10.1145/3643817openalex-snapshot
GMS-3DQA: Projection-Based Grid Mini-patch Sampling for 3D Model Quality Assessment
inferred← citeshttps://doi.org/10.1145/3664199openalex-snapshot
Blind Quality Assessment of Dense 3D Point Clouds with Structure Guided Resampling
inferred← citeshttps://doi.org/10.1145/3672567openalex-snapshot
Compressed Point Cloud Quality Index by Combining Global Appearance and Local Details
inferred← citeshttps://doi.org/10.1145/3696409.3700162openalex-snapshot
MS-GeodesicPSIM: Predicting the Quality of Static Mesh with Texture Map via multi-scale Geodesic Patch Similarity
inferred← citeshttps://doi.org/10.1145/3697351openalex-snapshot
Occupancy Map Guided Attributes Artifacts Removal for Video-Based Point Cloud Compression
inferred← citeshttps://doi.org/10.1145/3705321openalex-snapshot
Solutions, Challenges, and Opportunities in Volumetric Video Streaming: An Architectural Perspective
inferred← citeshttps://doi.org/10.1145/3711817openalex-snapshot
3D-DaVa: Enhancing 3D Point Cloud Data Reliability for Industrial Applications
inferred← citeshttps://doi.org/10.1145/3715134openalex-snapshot
MM-PCQA+: Advancing Multi-Modal Learning for Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.1145/3715916openalex-snapshot
Compression Approaches for LiDAR Point Clouds and Beyond: A Survey
inferred← citeshttps://doi.org/10.1145/3718742openalex-snapshot
PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds
inferred← citeshttps://doi.org/10.1145/3722559openalex-snapshot
Quality Assessment in the Era of Large Models: A Survey
inferred← citeshttps://doi.org/10.1145/3728472openalex-snapshot
Implicit Representation-based Volumetric Video Streaming for Photorealistic Full-scene Experience
inferred← citeshttps://doi.org/10.1145/3784713.3784728openalex-snapshot
ORNet: No-reference Point Cloud Quality Assessment in an Ordinal Regression Way
inferred← citeshttps://doi.org/10.1364/ao.533718openalex-snapshot
Multi-view high-dynamic-range 3D reconstruction and point cloud quality evaluation based on dual-frame difference images
inferred← citeshttps://doi.org/10.1609/aaai.v39i6.32607openalex-snapshot
CLIP-PCQA: Exploring Subjective-Aligned Vision-Language Modeling for Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.18293/seke2023-185openalex-snapshot
No-Reference Point Cloud Quality Assessment via Weighted Patch Quality Prediction
inferred← citeshttps://doi.org/10.2139/ssrn.5383425openalex-snapshot
High-Fidelity Point Cloud Metrology of Complex Surfaces Under Dynamic Disturbances by Fusing Geometric and Material Physics
inferred← citeshttps://doi.org/10.24963/ijcai.2023/195openalex-snapshot
MM-PCQA: Multi-Modal Learning for No-reference Point Cloud Quality Assessment
inferred← citeshttps://doi.org/10.3389/fphy.2026.1881265openalex-snapshot
Early coding unit termination algorithm for video-based dynamic point cloud compression
inferred← citeshttps://doi.org/10.3389/frsip.2024.1420060openalex-snapshot
New challenges in point cloud visual quality assessment: a systematic review
inferred← citeshttps://doi.org/10.3390/aerospace10020110openalex-snapshot
Evaluating Airfoil Mesh Quality with Transformer
inferred← citeshttps://doi.org/10.3390/jimaging10060129openalex-snapshot
Point Cloud Quality Assessment Using a One-Dimensional Model Based on the Convolutional Neural Network
inferred← citeshttps://doi.org/10.3390/s25041111openalex-snapshot
Quality Evaluation for Colored Point Clouds Produced by Autonomous Vehicle Sensor Fusion Systems
inferred← citeshttps://doi.org/10.5194/isprs-archives-xlviii-1-w3-2023-153-2023openalex-snapshot
GEOMETRIC ACCURACY ANALYSIS BETWEEN NEURAL RADIANCE FIELDS (NERFS) AND TERRESTRIAL LASER SCANNING (TLS)
inferred← citeshttps://doi.org/10.55452/1998-6688-2026-23-1-22-36openalex-snapshot
ANALYSIS AND COMPARISON OF CONTAINER ORCHESTRATION TOOLS IN ON-PREMISES AND CLOUD INFRASTRUCTURE
inferred← citeshttps://doi.org/10.70675/f90cc53ezc254z4385za778z0a193fee136bopenalex-snapshot
Revising the use of deep learning for effective point clouds quality assessment
inferred← citeshttps://doi.org/10.7717/peerj-cs.2281openalex-snapshot
Intelligent accounting optimization method based on meta-heuristic algorithm and CNN
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