Anomaly Detection on UCF-Crime (test)
0.8724AUCBN-WVAD
Evaluation Results
| Method | Links | |
|---|---|---|
| BN-WVADSupervision=Weakly, Feature=I3D2023.11 | 0.8724 | |
| UR-DMUSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.02 | 0.8697 | |
| UR-DMUSupervision=Weakly, Venue=AAAI'23, Feature=I3D2023.11 | 0.8697 | |
| UMILCategory=WSVAD2023.03 | 0.8675 | |
| UR-DMUSupervision=Weakly, Venue=AAAI'23, Feature=I3D, Note=reproduced by the authors2023.11 | 0.8623 | |
| Completeness-and-Uncertainty Aware Pseudo Label EnhancementSupervised=Weakly, Feature=I3D2022.12 | 0.8622 | |
| CU-NetSupervision=Weakly, Venue=CVPR'23, Feature=I3D2023.11 | 0.8622 | |
| SASSupervision=Weakly, Venue=arXiv'23, Feature=I3D2023.11 | 0.8619 | |
| S3RSupervision=Weakly, Venue=ECCV'22, Feature=I3D2023.11 | 0.8599 | |
| MSLSupervision level=Weakly Supervised, Feature (RGB)=VideoSwin2023.02 | 0.8562 | |
| WSALsupervision=weakly-supervised2020.08 | 0.8538 | |
| WSALSupervised=Weakly, Feature=TSN2022.12 | 0.8538 | |
| WSALCategory=WSVAD2023.03 | 0.8538 | |
| MSLSupervised=Weakly, Feature=I3D2022.12 | 0.853 | |
| MSLSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.02 | 0.853 | |
| MSLSupervision=Weakly, Venue=AAAI'22, Feature=I3D2023.11 | 0.853 | |
| Wu et al.Supervised=Weakly, Feature=I3D, citation=[32]2022.12 | 0.8489 | |
| CRFDSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.02 | 0.8489 | |
| RTFMSupervised=Weakly, Feature=I3D2022.12 | 0.843 | |
| RTFMSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.02 | 0.843 | |
| RTFMCategory=WSVAD2023.03 | 0.843 | |
| RTFMSupervision=Weakly, Venue=ICCV'21, Feature=I3D2023.11 | 0.843 | |
| BN-SVPBackbone=I3D2022.03 | 0.8339 | |
| BN-SVPSupervised=Weakly, Feature=I3D2022.12 | 0.8339 | |
| CLAWSSupervised=Weakly, Feature=C3D2022.12 | 0.8303 | |
| CLAWSSupervision level=Weakly Supervised, Feature (RGB)=C3D2023.02 | 0.8303 | |
| CLAWSSupervision=Weakly, Venue=ECCV'20, Feature=C3D2023.11 | 0.8303 | |
| LaGoVADTraining-set=PreVAD+XD, Protocol=12025.03 | 0.8281 | |
| HL-Net2020.07 | 0.8244 | |
| Wu et al.Supervised=Weakly, Feature=I3D, citation=[34]2022.12 | 0.8244 | |
| HL-NetSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.02 | 0.8244 | |
| Wu et al.Category=WSVAD2023.03 | 0.8244 | |
| HL-NetSupervision=Weakly, Venue=ECCV'20, Feature=I3D2023.11 | 0.8244 | |
| OVVADTraining-set=AIGC+XD, Protocol=12025.03 | 0.8242 | |
| MISTSupervised=Weakly, Feature=I3D2022.12 | 0.823 | |
| MISTSupervision level=Weakly Supervised, Feature (RGB)=I3D2023.02 | 0.823 | |
| MISTSupervision=Weakly, Venue=CVPR'21, Feature=I3D2023.11 | 0.823 | |
| Zhong et al.supervision=weakly-supervised2020.08 | 0.8212 | |
| Zhong et al.Backbone=TSNRGB2022.03 | 0.8212 | |
| GCNSupervised=Weakly, Feature=TSN2022.12 | 0.8212 | |
| GCNSupervision level=Weakly Supervised, Feature (RGB)=TSN2023.02 | 0.8212 | |
| GCN-AnomalyCategory=WSVAD2023.03 | 0.8212 | |
| GCNSupervision=Weakly, Venue=CVPR'19, Feature=TSN2023.11 | 0.8212 | |
| State-of-the-art2026.05 | 0.8212 | |
| State-of-the-art2026.05 | 0.8212 | |
| LaGoVADTraining-set=PreVAD, Protocol=12025.03 | 0.8112 | |
| Zhong et al.Backbone=GCN (C3D)2022.03 | 0.8108 | |
| BaselineCategory=WSVAD2023.03 | 0.8067 | |
| LAVADTraining-set=-, Protocol=12025.03 | 0.8028 | |
| VadCLIPTraining-set=XD, Protocol=12025.03 | 0.8016 | |
| MMILBackbone=I3D2022.03 | 0.7968 | |
| VadCLIPTraining-set=PreVAD, Protocol=12025.03 | 0.7937 | |
| Zhu et al.supervision=weakly-supervised2020.08 | 0.791 | |
| Motion-AwareCategory=WSVAD2023.03 | 0.791 | |
| Zhu et al.Supervised=Weakly, Feature=AE2022.12 | 0.79 | |
| MASupervision level=Weakly Supervised, Feature (RGB)=PWC2023.02 | 0.79 | |
| Zhang et al.Supervised=Weakly, Feature=C3D2022.12 | 0.7866 | |
| IBLSupervision level=Weakly Supervised, Feature (RGB)=C3D2023.02 | 0.7866 | |
| Zhang et al.Category=WSVAD2023.03 | 0.7866 | |
| MultiDomainTraining-set=Multiple, Protocol=12025.03 | 0.7855 | |
| Zhong et al.Backbone=TSNOpticalFlow2022.03 | 0.7808 | |
| Li & VasconcelosBackbone=I3D2022.03 | 0.7795 | |
| Proposed Method (3D ResNet + constr. + new rank. loss)Backbone=3D ResNet, Loss Function=New ranking loss, Constraints=Yes2020.02 | 0.7667 | |
| Ilse et al.Backbone=I3D2022.03 | 0.7652 | |
| Sultani et al.Supervision level=Weakly Supervised, Feature (RGB)=I3D2023.02 | 0.7621 | |
| Sultani et al.Supervision=Weakly, Venue=CVPR'18, Feature=I3D2023.11 | 0.7621 | |
| Proposed Method (3D ResNet + constr. + loss)Backbone=3D ResNet, Loss Function=Standard loss, Constraints=Yes2020.02 | 0.7562 | |
| Sultani et al.2020.07 | 0.7551 | |
| Deep MIL Rankingconstraints=with constraints2018.01 | 0.7541 | |
| W. Sultani et al.2020.02 | 0.7541 | |
| Sultani et al.supervision=weakly-supervised2020.08 | 0.7541 | |
| MMILBackbone=C3D2022.03 | 0.7541 | |
| Sultani et al.Supervised=Weakly, Feature=C3D2022.12 | 0.7541 | |
| Sultani et al.Supervision level=Weakly Supervised, Feature (RGB)=C3D2023.02 | 0.7541 | |
| Sultani et al.Category=WSVAD2023.03 | 0.7541 | |
| Sultani et al.Supervision=Weakly, Venue=CVPR'18, Feature=C3D2023.11 | 0.7541 | |
| FPDMSupervision=Unsupervised, Venue=ICCV'23, Feature=Image2023.11 | 0.747 | |
| Deep MIL Rankingconstraints=without constraints2018.01 | 0.7444 | |
| GCLSupervision level=Unsupervised, Feature (RGB)=ResNext2023.02 | 0.742 | |
| GCLSupervision=Unsupervised, Venue=CVPR'23, Feature=ResNeXt2023.11 | 0.742 | |
| LLaVA1.5Training-set=-, Protocol=12025.03 | 0.7284 | |
| Sun et al.Supervised=Semi2022.12 | 0.727 | |
| GODSCategory=UVAD2023.03 | 0.7046 | |
| BODSCategory=UVAD2023.03 | 0.6826 | |
| Lu et al.2018.01 | 0.6551 | |
| C. Lu et al.2020.02 | 0.6551 | |
| Lu et al.2020.07 | 0.6551 | |
| Lu et al.trained with normal videos only=true2020.08 | 0.6551 | |
| Lu et al.Backbone=C3D2022.03 | 0.6551 | |
| Lu et al.Supervised=Semi, Feature=Dictionary2022.12 | 0.6551 | |
| Lu et al.Supervision level=Unsupervised, Feature (RGB)=N/A2023.02 | 0.6551 | |
| Lu et al.Category=UVAD2023.03 | 0.6551 | |
| Weakly-Supervised Spatiotemporal Anomaly Detection2026.05 | 0.63 | |
| Weakly-Supervised Spatiotemporal Anomaly DetectionSupervision Level=Weakly-supervised2026.05 | 0.63 | |
| Lu et al.Backbone=I3D2022.03 | 0.6198 | |
| Ionescu et al.Supervised=Semi2022.12 | 0.616 | |
| Sohrab et al.Category=UVAD2023.03 | 0.585 | |
| PELTraining-set=XD, Protocol=12025.03 | 0.5452 | |
| CLIPTraining-set=-, Protocol=12025.03 | 0.5316 | |
| Hasan et al.2018.01 | 0.506 |