Search Results for author:
Found 3 papers, 2 papers with code
Aligning First, Then Fusing: A Novel Weakly Supervised Multimodal Violence Detection Method
Weakly supervised violence detection refers to the technique of training models to identify violent segments in videos using only video-level labels.
Anomaly Detection In Surveillance Videos
Multiple Instance Learning
+1
Multi-view Distillation based on Multi-modal Fusion for Few-shot Action Recognition(CLIP-$\mathrm{M^2}$DF)
In each view, we fuse the prompt embedding as consistent information with visual and the global or local temporal context to overcome the overlapping distribution of classes and outliers.
ISSTAD: Incremental Self-Supervised Learning Based on Transformer for Anomaly Detection and Localization
In the subsequent stage, we apply pixel-level data augmentation techniques to generate corrupted normal images and their corresponding pixel labels.
Ranked #75 on
Anomaly Detection
on MVTec AD
(using extra training data)
