👉 3DQA Databases (update)

If you want to add PCQA papers and codes to this list, feel free to start a pull request.

We are happy to see your contribution!

Overview of the databases

Database	Format	Attributes	Rated Models
M-PCCD	Point cloud	Colored	232
IRPC	Point cloud	Colorless & Colored	54 & 54
WPC	Point cloud	Colored	740
WPC2.0	Point cloud	Colored	400
WPC3.0	Point cloud	Colored	350
ICIP2020	Point cloud	Colored	96
SJTU-PCQA	Point cloud	Colored	378
SIAT-PCQD	Point cloud	Colored	340
LS-PCQA	Point cloud	Colored	1,080
BASICS	Point cloud	Colored	1,494
CMDM	Mesh	Colored	480
TMQA	Mesh	Textured	3,000
Geo-Metric	Mesh	Geometry Faces	2,450
DHHQA	Mesh	Textured human heads	1,540
DDH-QA	FBX/MP4	Dynamic Digital Humans	800
SJTU-H3D	Mesh	Full-body Digital Humans	1,120

PCQA databases

#	Database Name	Title & Link	Database Link
1	SJTU-PCQA	Predicting the Perceptual Quality of Point Cloud: A 3D-to-2D Projection-Based Exploration	Link
2	WPC	Perceptual Quality Assessment of Colored 3D Point Clouds	Link
3	LS-PCQA	Point Cloud Quality Assessment: Dataset Construction and Learning-based No-Reference Approach	Link
4	WPC2.0(Compression)	Reduced Reference Perceptual Quality Model with Application to Rate Control for Video-based Point Cloud Compression	Link
5	WPC3.0(Compression)	No-reference Bitstream-layer Model for Perceptual Quality Assessment of V-PCC Encoded Point Clouds	Link
6	CPCD2.0(Compression & Noise)	TGP-PCQA: Texture and geometry projection based quality assessment for colored point clouds	Link
7	ICIP2020	Quality Evaluation Of Static Point Clouds Encoded Using MPEG Codecs
8	M-PCCD	A comprehensive study of the rate-distortion performance in MPEG point cloud compression
9	IRPC	Point Cloud Rendering after Coding : Impacts on Subjective and Objective Quality.
10	SIAT-PCQD	Subjective Quality Database and Objective Study of Compressed Point Clouds With 6DoF Head-Mounted Display	Link
11	vsenseVVDB (Volumetric Video Quality Database #1)	Subjective and Objective Quality Assessment for Volumetric Video Compression	Link
12	vsenseVVDB2 (Volumetric Video Quality Database #2)	Textured mesh vs coloured point cloud: A subjective study for volumetric video compression	Link
13	BASICS	BASICS: Broad quality Assessment of Static point clouds In Compression Scenarios

MQA (mesh quality assessment) database

#	Database Name	Title & Link	Database Link
1	CMDM	Visual Quality of 3D Meshes With Diffuse Colors in Virtual Reality: Subjective and Objective Evaluation	Link
2	TMQA	Textured Mesh Quality Assessment: Large-Scale Dataset and Deep Learning-based Quality Metric	Link
3	-	Geo-Metric: A Perceptual Dataset of Distortions on Faces	link
4	SJTU-TMQA	SJTU-TMQA: A quality assessment database for static mesh with texture map	link

Digital human quality assessment database

#	Database Name	Title & Link	Database Link
1	DHHQA	Perceptual Quality Assessment for Digital Human Heads	Link
2	DDH-QA	DDH-QA: A DYNAMIC DIGITAL HUMANS QUALITY ASSESSMENT DATABASE	Link
3	SJTU-H3D	Advancing Zero-Shot Digital Human Quality Assessment through Text-Prompted Evaluation	Link

👉 3DQA methods

Basic FR-PCQA

Basic full-reference quality assessment metrics implemented by Python.

I try to implement the p2point, p2plane, and PSNR_yuv with python. The original algorithms come from "Evaluation criteria for PCC (Point Cloud Compression)","Dynamic Polygon Clouds: Representation and Compression for VR/AR", and "Geometric Distortion Metrics for Point Cloud Compression".

FR-PCQA metrics

#	Metric Name	Title & Link	Code Link
1	PointSSIM	"Towards a Point Cloud Structural Similarity Metric"	Code
2	GraphSIM	"Inferring Point Cloud Quality via Graph Similarity"	Code
3	PCQM	"PCQM: A Full-Reference Quality Metric for Colored 3D Point Clouds"	Code

RR-PCQA metrics

#	Metric Name	Title & Link	Code Link
1	PCMrr	"A Reduced Reference Metric for Visual Quality Evaluation of Point Cloud Contents"	Code
2	-	"Reduced Reference Quality Assessment for Point Cloud Compression"	-
3	-	"Reduced-Reference Quality Assessment of Point Clouds via Content-Oriented Saliency Projection"	Code
4	-	"Support Vector Regression-based Reduced-Reference Perceptual Quality Model for Compressed Point Clouds"

NR-PCQA metrics

#	Metric Name	Title & Link	Code Link
1	3D-NSS	"No-Reference Quality Assessment for 3D Colored Point Cloud and Mesh Models" [Arxiv]	Code
2	ResSCNN	"Point Cloud Quality Assessment: Dataset Construction and Learning-based No-Reference Approach"	Code
3	IT-PCQA	"No-Reference Point Cloud Quality Assessment via Domain Adaptation"	Code
4	3D-CNN-PCQA	"A No-reference Quality Assessment Metric for Point Cloud Based on Captured Video Sequences"	-
5	VQA-PC	"Evaluating Point Cloud from Moving Camera Videos: A No-Reference Metric"	Code
6	-	"Blind Quality Assessment of 3D Dense Point Clouds with Structure Guided Resampling"	-
7	MM-PCQA	"MM-PCQA: Multi-Modal Learning for No-reference Point Cloud Quality Assessment"	Code
8	-	"V-PCC Projection Based Blind Point Cloud Quality Assessment for Compression Distortion"	-
9	-	"GPA-Net: No-Reference Point Cloud Quality Assessment with Multi-task Graph Convolutional Network"	Code
10	-	"PQA-Net: Deep No Reference Point Cloud Quality Assessment via Multi-View Projection"	Code
11	-	"Progressive Knowledge Transfer Based on Human Visual Perception Mechanism for Perceptual Quality Assessment of Point Clouds"	-
12	-	"Bitstream-based Perceptual Quality Assessment of Compressed 3D Point Clouds"	-
13	-	"GMS-3DQA: Projection-based Grid Mini-patch Sampling for 3D Model Quality Assessment"	Code
14	-	"Once-Training-All-Fine: No-Reference Point Cloud Quality Assessment via Domain-relevance Degradation Description"	-
15	-	"Pseudo-Reference Point Cloud Quality Measurement Based on Joint 2-D and 3-D Distortion Description"	-
16	-	"pmBQA: Projection-based Blind Point Cloud Quality Assessment via Multimodal Learning"	-
17	-	"Non-Local Geometry and Color Gradient Aggregation Graph Model for No-Reference Point Cloud Quality Assessment"	-
18	-	"Simple Baselines for Projection-based Full-reference and No-reference Point Cloud Quality Assessment"	-
19	-	"Plain-PCQA: No-Reference Point Cloud Quality Assessment by Analysis of Plain Visual and Geometrical Components"	-
20	-	"Zoom to Perceive Better: No-reference Point Cloud Quality Assessment via Exploring Effective Multiscale Feature"	Code
21	-	"PAME: SELF-SUPERVISED MASKED AUTOENCODER FOR NO-REFERENCE POINT CLOUD QUALITY ASSESSMENT"	-
22	-	"Contrastive Pre-Training with Multi-View Fusion for No-Reference Point Cloud Quality Assessment"	-
23	-	"MFT-PCQA: Multi-Modal Fusion Transformer for No-Reference Point Cloud Quality Assessment"	-
24	-	"Rating-Augmented No-Reference Point Cloud Quality Assessment Using Multi-Task Learning"	-
25	-	"3DTA: No-Reference 3D Point Cloud Quality Assessment with Twin Attention"	Code
26	-	"Compressed Point Cloud Quality Index by Combining Global Appearance and Local Details"	-
27	-	"Asynchronous Feedback Network for Perceptual Point Cloud Quality Assessment"	Code
28	-	"TCDM: Transformational Complexity Based Distortion Metric for Perceptual Point Cloud Quality Assessment	Code
29	ACM MM Best Paper Nomination	"LMM-PCQA: Assisting Point Cloud Quality Assessment with LMM"	Code
30	-	"LLM-guided Cross-Modal Point Cloud Quality Assessment: A Graph Learning Approach"	-
31	-	"Visual-Saliency Guided Multi-modal Learning for No Reference Point Cloud Quality Assessment"	-
32	-	"Perceptual Quality Assessment of Trisoup-Lifting Encoded 3D Point Clouds"	-
33	-	"No-Reference Point Cloud Quality Assessment Through Structure Sampling and Clustering Based on Graph"	-
34	-	"No-reference point cloud quality assessment via graph convolutional network"	-

Mesh QA metrics

1. "Surface-Sampling Based Objective Quality Assessment Metrics for Meshes" [ICASSP]

Contact Information

😎 If you want to make contributions, include your works, or simply make discussions, feel free to e-mail me at [email protected] 😎

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