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ResearchFormerly WizWand

Anomaly Detection on UCF-Crime (test)

0.8724AUCBN-WVAD
0.4913440.5902720.68920.788128Jan 12, 2018Jun 3, 2019Oct 22, 2020Mar 13, 2022Aug 2, 2023Dec 21, 2024May 13, 2026
Updated 5mo ago

Evaluation results

MethodLinks
BN-WVADSupervision=Weakly, Feature=I3D2023.110.8724
UR-DMUSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.020.8697
UR-DMUSupervision=Weakly, Venue=AAAI'23, Feature=I3D2023.110.8697
UMILCategory=WSVAD2023.030.8675
UR-DMUSupervision=Weakly, Venue=AAAI'23, Feature=I3D, Note=reproduced by the authors2023.110.8623
Completeness-and-Uncertainty Aware Pseudo Label EnhancementSupervised=Weakly, Feature=I3D2022.120.8622
CU-NetSupervision=Weakly, Venue=CVPR'23, Feature=I3D2023.110.8622
SASSupervision=Weakly, Venue=arXiv'23, Feature=I3D2023.110.8619
S3RSupervision=Weakly, Venue=ECCV'22, Feature=I3D2023.110.8599
MSLSupervision level=Weakly Supervised, Feature (RGB)=VideoSwin2023.020.8562
WSALsupervision=weakly-supervised2020.080.8538
WSALSupervised=Weakly, Feature=TSN2022.120.8538
WSALCategory=WSVAD2023.030.8538
MSLSupervised=Weakly, Feature=I3D2022.120.853
MSLSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.020.853
MSLSupervision=Weakly, Venue=AAAI'22, Feature=I3D2023.110.853
Wu et al.Supervised=Weakly, Feature=I3D, citation=[32]2022.120.8489
CRFDSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.020.8489
RTFMSupervised=Weakly, Feature=I3D2022.120.843
RTFMSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.020.843
RTFMCategory=WSVAD2023.030.843
RTFMSupervision=Weakly, Venue=ICCV'21, Feature=I3D2023.110.843
BN-SVPBackbone=I3D2022.030.8339
BN-SVPSupervised=Weakly, Feature=I3D2022.120.8339
CLAWSSupervised=Weakly, Feature=C3D2022.120.8303
CLAWSSupervision level=Weakly Supervised, Feature (RGB)=C3D2023.020.8303
CLAWSSupervision=Weakly, Venue=ECCV'20, Feature=C3D2023.110.8303
LaGoVADTraining-set=PreVAD+XD, Protocol=12025.030.8281
HL-Net2020.070.8244
Wu et al.Supervised=Weakly, Feature=I3D, citation=[34]2022.120.8244
HL-NetSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.020.8244
Wu et al.Category=WSVAD2023.030.8244
HL-NetSupervision=Weakly, Venue=ECCV'20, Feature=I3D2023.110.8244
OVVADTraining-set=AIGC+XD, Protocol=12025.030.8242
MISTSupervised=Weakly, Feature=I3D2022.120.823
MISTSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.020.823
MISTSupervision=Weakly, Venue=CVPR'21, Feature=I3D2023.110.823
Zhong et al.supervision=weakly-supervised2020.080.8212
Zhong et al.Backbone=TSNRGB2022.030.8212
GCNSupervised=Weakly, Feature=TSN2022.120.8212
GCNSupervision level=Weakly Supervised, Feature (RGB)=TSN2023.020.8212
GCN-AnomalyCategory=WSVAD2023.030.8212
GCNSupervision=Weakly, Venue=CVPR'19, Feature=TSN2023.110.8212
State-of-the-art2026.050.8212
State-of-the-art2026.050.8212
LaGoVADTraining-set=PreVAD, Protocol=12025.030.8112
Zhong et al.Backbone=GCN (C3D)2022.030.8108
BaselineCategory=WSVAD2023.030.8067
LAVADTraining-set=-, Protocol=12025.030.8028
VadCLIPTraining-set=XD, Protocol=12025.030.8016
MMILBackbone=I3D2022.030.7968
VadCLIPTraining-set=PreVAD, Protocol=12025.030.7937
Zhu et al.supervision=weakly-supervised2020.080.791
Motion-AwareCategory=WSVAD2023.030.791
Zhu et al.Supervised=Weakly, Feature=AE2022.120.79
MASupervision level=Weakly Supervised, Feature (RGB)=PWC2023.020.79
Zhang et al.Supervised=Weakly, Feature=C3D2022.120.7866
IBLSupervision level=Weakly Supervised, Feature (RGB)=C3D2023.020.7866
Zhang et al.Category=WSVAD2023.030.7866
MultiDomainTraining-set=Multiple, Protocol=12025.030.7855
Zhong et al.Backbone=TSNOpticalFlow2022.030.7808
Li & VasconcelosBackbone=I3D2022.030.7795
Proposed Method (3D ResNet + constr. + new rank. loss)Backbone=3D ResNet, Loss Function=New ranking loss, Constraints=Yes2020.020.7667
Ilse et al.Backbone=I3D2022.030.7652
Sultani et al.Supervision level=Weakly Supervised, Feature (RGB)=I3D2023.020.7621
Sultani et al.Supervision=Weakly, Venue=CVPR'18, Feature=I3D2023.110.7621
Proposed Method (3D ResNet + constr. + loss)Backbone=3D ResNet, Loss Function=Standard loss, Constraints=Yes2020.020.7562
Sultani et al.2020.070.7551
Deep MIL Rankingconstraints=with constraints2018.010.7541
W. Sultani et al.2020.020.7541
Sultani et al.supervision=weakly-supervised2020.080.7541
MMILBackbone=C3D2022.030.7541
Sultani et al.Supervised=Weakly, Feature=C3D2022.120.7541
Sultani et al.Supervision level=Weakly Supervised, Feature (RGB)=C3D2023.020.7541
Sultani et al.Category=WSVAD2023.030.7541
Sultani et al.Supervision=Weakly, Venue=CVPR'18, Feature=C3D2023.110.7541
FPDMSupervision=Unsupervised, Venue=ICCV'23, Feature=Image2023.110.747
Deep MIL Rankingconstraints=without constraints2018.010.7444
GCLSupervision level=Unsupervised, Feature (RGB)=ResNext2023.020.742
GCLSupervision=Unsupervised, Venue=CVPR'23, Feature=ResNeXt2023.110.742
LLaVA1.5Training-set=-, Protocol=12025.030.7284
Sun et al.Supervised=Semi2022.120.727
GODSCategory=UVAD2023.030.7046
BODSCategory=UVAD2023.030.6826
Lu et al.2018.010.6551
C. Lu et al.2020.020.6551
Lu et al.2020.070.6551
Lu et al.trained with normal videos only=true2020.080.6551
Lu et al.Backbone=C3D2022.030.6551
Lu et al.Supervised=Semi, Feature=Dictionary2022.120.6551
Lu et al.Supervision level=Unsupervised, Feature (RGB)=N/A2023.020.6551
Lu et al.Category=UVAD2023.030.6551
Weakly-Supervised Spatiotemporal Anomaly Detection2026.050.63
Weakly-Supervised Spatiotemporal Anomaly DetectionSupervision Level=Weakly-supervised2026.050.63
Lu et al.Backbone=I3D2022.030.6198
Ionescu et al.Supervised=Semi2022.120.616
Sohrab et al.Category=UVAD2023.030.585
PELTraining-set=XD, Protocol=12025.030.5452
CLIPTraining-set=-, Protocol=12025.030.5316
Hasan et al.2018.010.506