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Point Cloud Quality Assessment research benchmarks – Page 2 · SOTA2 Research

Point Cloud Quality Assessment

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

SJTU-PCQA Type 6 geometry gaussian noise

0.938SRCC

11

Feb 26, 2026

SJTU-PCQA Type 5 downsampling & geometry gaussian noise

0.962SRCC

11

Feb 26, 2026

SJTU-PCQA Type 4 downsampling & color noise

0.957SRCC

11

Feb 26, 2026

SJTU-PCQA Type 3 (downsampling)

0.921SRCC

11

Feb 26, 2026

SJTU-PCQA Type 2 color noise

0.852SRCC

11

Feb 26, 2026

Dataset D (test)

100Pair-wise Ranking Accuracy (GN)

8

Apr 21, 2026

WPC (target) trained on KADID-10k (source) cross-domain (test)

0.553PLCC

7

Mar 5, 2026

SJTU-PCQA cross-domain (target) trained on KADID-10k (source) (test)

0.843PLCC

7

Mar 5, 2026

WPC TID2013 (test)

0.563PLCC

7

Mar 5, 2026

SJTU-PCQA TID2013 (test)

0.842PLCC

7

Mar 5, 2026

Waterloo Point Cloud (WPC) database (test)

0.932PLCC

7

Feb 26, 2026

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