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SOTA
Video Retrieval
Video Retrieval On Fivr 200K
Video Retrieval On Fivr 200K
Métriques
mAP (CSVR)
mAP (DSVR)
mAP (ISVR)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
mAP (CSVR)
mAP (DSVR)
mAP (ISVR)
Paper Title
Repository
ViSiLf
0.797
0.843
0.660
ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
TCAc
0.553
0.570
0.473
Temporal Context Aggregation for Video Retrieval with Contrastive Learning
DnS (S^f_B)
0.863
0.909
0.729
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
ViSiLsym
0.792
0.833
0.654
ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
VRAG (CS)
0.678
0.723
0.554
VRAG: Region Attention Graphs for Content-Based Video Retrieval
-
ViSiLv (pt)
0.854
0.899
0.723
ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
DnS (S^c)
0.558
0.574
0.476
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
S2VS
0.879
0.927
0.746
Self-Supervised Video Similarity Learning
Jo et al. (SCFV+TNIP)
0.833
0.896
0.674
Exploring the Temporal Cues to Enhance Video Retrieval on Standardized CDVA
TCAf
0.830
0.877
0.703
Temporal Context Aggregation for Video Retrieval with Contrastive Learning
TCAsym
0.698
0.728
0.592
Temporal Context Aggregation for Video Retrieval with Contrastive Learning
ViSiLv (tf)
0.841
0.892
0.702
ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
VVS
0.689
0.711
0.590
VVS: Video-to-Video Retrieval with Irrelevant Frame Suppression
S2VS
0.878
0.925
0.739
Self-Supervised Video Similarity Learning
DnS (S^f_A)
0..875
0.921
0.741
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
VRAG (video)
0.470
0.484
0.399
VRAG: Region Attention Graphs for Content-Based Video Retrieval
-
LAMV
0.466
0.496
0.371
LAMV: Learning to Align and Match Videos With Kernelized Temporal Layers
0 of 17 row(s) selected.
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