Papers for Video Anomaly Detection, released codes collection, Performance Comparision.
Papers for Video Anomaly Detection, released codes collections.
Any addition or bug please open an issue, pull requests or e-mail me by
[email protected]
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Download_link, Ano-Locality
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The Datasets belowed are about Traffic Accidents Anticipating in Dashcam videos or Surveillance videos
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CVPR 16. Code ### 2017
ICCV 2017. (Explainable VAD)
ICCV 2017. code
ICME 2017.Code
ACM MM 17.
ICCV 17.
CVPR 2018. code
CVPR 2018. code
ACM MM 18.
ICCV 2019.code
CVPR 2019.code
CVPR 2019.
ICCV 2019.code
WACV 2020.
WACV 2020.
CVPR 2020.code
CVPR 2020.
CVPR 2020. code
CVPR 2020 Worksop.
CVPR 2020. code
CVPR 2020 workshop.
ECCV 2020 Spotlightcode
ECCV 2020
ACM MM 2020 Oralcode
ACCV 2020
ACM MM 2020
ACM MM 2020
CVPR 2018code ### 2019
CVPR 2019, code
IJCAI 2019code.
ICIP 19.
BMVC 19. ### 2020
WACV 2020.
ICME 2020.code
ECCV 2020
ECCV 2020
ACM MM 19.
ECCV 2020code
Generally, anomaly detection in recent researches are based on the datasets from pedestrian (likes UCSD, Avenue, ShanghaiTech, etc.), or UCF-Crime (real-world anomaly). However some focus on specific scene as follows.
CVPR workshop, AI City Challenge series.
Unsupervised Traffic Accident Detection in First-Person Videos, IROS 2019.
When, Where, and What? A New Dataset for Anomaly Detection in Driving Videos. github
| Model | Reported on Convference/Journal | Supervised | Feature | End2End | 32 Segments | AUC (%) | [email protected] on Normal (%) | | --------------------------------------------------- | ------------------------------- | ---------- | -------- | ------- | ----------- | ------- | --------------------- | | Sultani.etl | CVPR 18 | Weakly | C3D RGB | X | √ | 75.41 | 1.9 | | IBL | ICIP 19 | Weakly | C3D RGB | X | √ | 78.66 | - | | Motion-Aware | BMVC 19 | Weakly | PWC Flow | X | √ | 79.0 | - | | GCN-Anomaly | CVPR 19 | Weakly | TSN RGB | √ | X | 82.12 | 0.1 | | ST-Graph | ACM MM 20 | Un | - | √ | X | 72.7 | | | Background-Bias | ACM MM 19 | Fully | NLN RGB | √ | X | 82.0 | - | | CLAWS | ECCV 20 | Weakly | C3D RGB | √ | X | 83.03 | - |
| Model | Reported on Conference/Journal | Supervision | Feature | End2End | AUC(%) | [email protected] (%) | | ------------------------------------------------- | ------------------------------ | ----------------------------- | ------------------ | ------- | ------ | ----------- | | Conv-AE | CVPR 16 | Un | - | √ | 60.85 | - | | stacked-RNN | ICCV 17 | Un | - | √ | 68.0 | - | | FramePred | CVPR 18 | Un | - | √ | 72.8 | - | | FramePred* | IJCAI 19 | Un | - | √ | 73.4 | - | | Mem-AE | ICCV 19 | Un | - | √ | 71.2 | - | | MNAD | CVPR 20 | Un | - | √ | 70.5 | - | | VEC | ACM MM 20 | Un | - | √ | 74.8 | - | | ST-Graph | ACM MM 20 | Un | - | √ | 74.7 | - | | CAC | ACM MM 20 | Un | - | √ | 79.3 | | | MLEP | IJCAI 19 | 10% test vids with Video Anno | - | √ | 75.6 | - | | MLEP | IJCAI 19 | 10% test vids with Frame Anno | - | √ | 76.8 | - | | Sultani.etl | ICME 2020 | Weakly (Re-Organized Dataset) | C3D-RGB | X | 86.3 | 0.15 | | IBL | ICME 2020 | Weakly (Re-Organized Dataset) | I3D-RGB | X | 82.5 | 0.10 | | GCN-Anomaly | CVPR 19 | Weakly (Re-Organized Dataset) | C3D-RGB | √ | 76.44 | - | | GCN-Anomaly | CVPR 19 | Weakly (Re-Organized Dataset) | TSN-Flow | √ | 84.13 | - | | GCN-Anomaly | CVPR 19 | Weakly (Re-Organized Dataset) | TSN-RGB | √ | 84.44 | - | | AR-Net | ICME 20 | Weakly (Re-Organized Dataset) | I3D-RGB & I3D Flow | X | 91.24 | 0.10 | | CLAWS | ECCV 20 | Weakly (Re-Organized Dataset) | C3D-RGB | √ | 89.67 | |
| Model | Reported on Conference/Journal | Supervision | Feature | End2End | AUC(%) | | ------------------------------------------------------------ | ------------------------------ | ----------------------------- | ---------------------- | ------- | ------ | | Conv-AE | CVPR 16 | Un | - | √ | 70.2 | | Conv-AE* | CVPR 18 | Un | - | √ | 80.0 | | ConvLSTM-AE | ICME 17 | Un | - | √ | 77.0 | | DeepAppearance | ICAIP 17 | Un | - | √ | 84.6 | | Unmasking | ICCV 17 | Un | 3D gradients+VGG conv5 | X | 80.6 | | stacked-RNN | ICCV 17 | Un | - | √ | 81.7 | | FramePred | CVPR 18 | Un | - | √ | 85.1 | | Mem-AE | ICCV 19 | Un | - | √ | 83.3 | | Appearance-Motion Correspondence | ICCV 19 | Un | - | √ | 86.9 | | FramePred* | IJCAI 19 | Un | - | √ | 89.2 | | MNAD | CVPR 20 | Un | - | √ | 88.5 | | VEC | ACM MM 20 | Un | - | √ | 90.2 | | ST-Graph | ACM MM 20 | Un | - | √ | 89.6 | | CAC | ACM MM 20 | Un | - | √ | 87.0 | | MLEP | IJCAI 19 | 10% test vids with Video Anno | - | √ | 91.3 | | MLEP | IJCAI 19 | 10% test vids with Frame Anno | - | √ | 92.8 |