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Video Person Re-identification on CCVID

97.08Top-1 AccuracyGaitCLIF
56.124866.757477.3988.0226Apr 14, 2022Dec 13, 2022Aug 14, 2023Apr 13, 2024Dec 13, 2024Aug 13, 2025Apr 14, 2026

Evaluation results

MethodLinks
GaitCLIFInput=128 x 88 RGB images, Sampling=8 frames2026.0497.08—
InsightFace2022.1195.3—
DeepGaitV2Input=128 x 88 RGB images, Sampling=8 frames2026.0493.18—
CAL + GEFFGallery Enrichment=Enabled2022.1189.2—
DCR-ReID2022.1184.7—
AP3D + CALtesting frame selection=all frames, additional loss=Clothes-based Adversarial Loss2022.0483.680
Non-Local + CALtesting frame selection=all frames, additional loss=Clothes-based Adversarial Loss2022.048380.2
CAL2022.1182.9—
TCLNet + CALtesting frame selection=all frames, additional loss=Clothes-based Adversarial Loss2022.0482.179.6
CALtesting frame selection=all frames2022.0481.779.6
TCLNet2022.1181.4—
AP3D2022.1180.9—
I3D + CALtesting frame selection=all frames, additional loss=Clothes-based Adversarial Loss2022.0480.878.6
TCLNettesting frame selection=all frames2022.0480.775.9
Non-Local2022.1180.7—
AP3Dtesting frame selection=all frames2022.0480.177.7
I3D2022.1179.7—
Non-Localtesting frame selection=all frames2022.0479.376.2
I3Dtesting frame selection=all frames2022.0478.575.3
baselinetesting frame selection=all frames2022.0477.373.9
CTL2022.1171.8—
GaitSettesting frame selection=all frames2022.047162.1
baseline(F)testing frame selection=first frame only2022.0463.156.3
GaitNettesting frame selection=all frames2022.0457.749