Search Results for author:
Found 4 papers, 4 papers with code
Attribute-based Representations for Accurate and Interpretable Video Anomaly Detection
Surprisingly, we find that this simple representation is sufficient to achieve state-of-the-art performance in ShanghaiTech, the largest and most complex VAD dataset.
Ranked #1 on
Abnormal Event Detection In Video
on UCSD Ped2
Anomaly Detection Requires Better Representations
Anomaly detection seeks to identify unusual phenomena, a central task in science and industry.
Ranked #1 on
Anomaly Detection
on ODDS
3D Anomaly Detection and Segmentation
Representation Learning
+1
Mean-Shifted Contrastive Loss for Anomaly Detection
We take the approach of transferring representations pre-trained on external datasets for anomaly detection.
Ranked #3 on
Anomaly Detection
on One-class CIFAR-100
(using extra training data)
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
In recent years, the anomaly detection community has attempted to obtain better features using advances in deep self-supervised feature learning.
Ranked #1 on
Anomaly Detection
on Cats-and-Dogs
