MADRI detects anomalies in human-robot pick-and-place tasks by reconstructing multimodal feature vectors from video, internal sensors, and scene graphs, with multimodal versions outperforming vision-only on a custom dataset.
Memorizing normality to detect anomaly: Memory-augmented deep autoencoder for unsupervised anomaly detection
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Multimodal Anomaly Detection for Human-Robot Interaction
MADRI detects anomalies in human-robot pick-and-place tasks by reconstructing multimodal feature vectors from video, internal sensors, and scene graphs, with multimodal versions outperforming vision-only on a custom dataset.