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Found 4 papers, 4 papers with code
MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection
Weakly supervised video anomaly detection (WS-VAD) is to distinguish anomalies from normal events based on discriminative representations.
Cross-modal Consensus Network for Weakly Supervised Temporal Action Localization
In this work, we argue that the features extracted from the pretrained extractor, e. g., I3D, are not the WS-TALtask-specific features, thus the feature re-calibration is needed for reducing the task-irrelevant information redundancy.
Weakly Supervised Action Localization
Weakly-supervised Temporal Action Localization
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Cross-modal Consensus Network forWeakly Supervised Temporal Action Localization
In this work, we argue that the features extracted from the pretrained extractor, e. g., I3D, are not the WS-TALtask-specific features, thus the feature re-calibration is needed for reducing the task-irrelevant information redundancy.
Weakly-supervised Temporal Action Localization
Weakly Supervised Temporal Action Localization
Weakly-Supervised Temporal Action Localization by Progressive Complementary Learning
Accordingly, we first exclude these surely non-existent categories by a complementary learning loss.
