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Models/Conv-AE

Conv-AE

Reported on 8 benchmarks across 4 tasks · 1 paper · 8 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision6 results

  • Traffic Accident DetectiononSA
    AUC· 2016-04-15
    50.4
    best: 55.6 (FOL-MaxSTD (pred only))
    SOTA
    Learning Temporal Regularity in Video SequencesarXiv:1604.04574
  • Traffic Accident DetectiononA3D
    AUC· 2016-04-15
    49.5
    best: 60.1 (FOL-MaxSTD (pred only))
    SOTA
    Learning Temporal Regularity in Video SequencesarXiv:1604.04574
  • 3D Anomaly DetectiononHR-ShanghaiTech
    AUC· 2016-04-15
    69.8
    best: 87.23 (PoseWatch-H)
    SOTA
    Learning Temporal Regularity in Video SequencesarXiv:1604.04574
  • 3D Anomaly DetectiononHR-Avenue
    AUC· 2016-04-15
    84.8
    best: 89.4 (TrajREC)
    SOTA
    Learning Temporal Regularity in Video SequencesarXiv:1604.04574
  • Video Anomaly DetectiononHR-ShanghaiTech
    AUC· 2016-04-15
    69.8
    best: 87.23 (PoseWatch-H)
    SOTA
    Learning Temporal Regularity in Video SequencesarXiv:1604.04574
  • Video Anomaly DetectiononHR-Avenue
    AUC· 2016-04-15
    84.8
    best: 89.4 (TrajREC)
    SOTA
    Learning Temporal Regularity in Video SequencesarXiv:1604.04574

Methodology2 results

  • Anomaly DetectiononHR-ShanghaiTech
    AUC· 2016-04-15
    69.8
    best: 87.23 (PoseWatch-H)
    SOTA
    Learning Temporal Regularity in Video SequencesarXiv:1604.04574
  • Anomaly DetectiononHR-Avenue
    AUC· 2016-04-15
    84.8
    best: 89.4 (TrajREC)
    SOTA
    Learning Temporal Regularity in Video SequencesarXiv:1604.04574