HyperAI
HyperAI초신경
홈
플랫폼
문서
뉴스
연구 논문
튜토리얼
데이터셋
백과사전
SOTA
LLM 모델
GPU 랭킹
컨퍼런스
전체 검색
소개
서비스 약관
개인정보 처리방침
한국어
HyperAI
HyperAI초신경
Toggle Sidebar
전체 사이트 검색...
⌘
K
Command Palette
Search for a command to run...
플랫폼
홈
SOTA
비디오 검색
Video Retrieval On Fivr 200K
Video Retrieval On Fivr 200K
평가 지표
mAP (CSVR)
mAP (DSVR)
mAP (ISVR)
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
mAP (CSVR)
mAP (DSVR)
mAP (ISVR)
Paper Title
S2VS
0.879
0.927
0.746
Self-Supervised Video Similarity Learning
S2VS
0.878
0.925
0.739
Self-Supervised Video Similarity Learning
DnS (S^f_B)
0.863
0.909
0.729
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
ViSiLv (pt)
0.854
0.899
0.723
ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
ViSiLv (tf)
0.841
0.892
0.702
ViSiL: Fine-grained Spatio-Temporal 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
ViSiLf
0.797
0.843
0.660
ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
ViSiLsym
0.792
0.833
0.654
ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning
TCAsym
0.698
0.728
0.592
Temporal Context Aggregation for Video Retrieval with Contrastive Learning
VVS
0.689
0.711
0.590
VVS: Video-to-Video Retrieval with Irrelevant Frame Suppression
VRAG (CS)
0.678
0.723
0.554
VRAG: Region Attention Graphs for Content-Based Video Retrieval
DnS (S^c)
0.558
0.574
0.476
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
TCAc
0.553
0.570
0.473
Temporal Context Aggregation for Video Retrieval with Contrastive Learning
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
DnS (S^f_A)
0..875
0.921
0.741
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval
0 of 17 row(s) selected.
Previous
Next