1 citations · 2 across the 11 of their papers we have counts for
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3D Human-Human Interaction Anomaly Detection
Shun Maeda, Chunzhi Gu, Koichiro Kamide +3
Human-centric anomaly detection (AD) has been primarily studied to specify anomalous behaviors in a single person. However, as humans by nature tend to act in a collaborative manne…
Few-shot Human Action Anomaly Detection via a Unified Contrastive Learning Framework
Koichiro Kamide, Shunsuke Sakai, Shun Maeda +2
Human Action Anomaly Detection (HAAD) aims to identify anomalous actions given only normal action data during training. Existing methods typically follow a one-model-per-category p…
3DKeyAD: High-Resolution 3D Point Cloud Anomaly Detection via Keypoint-Guided Point Clustering
Zi Wang, Katsuya Hotta, Koichiro Kamide +3
High-resolution 3D point clouds are highly effective for detecting subtle structural anomalies in industrial inspection. However, their dense and irregular nature imposes significa…
Label-Consistent Dataset Distillation with Detector-Guided Refinement
Yawen Zou, Guang Li, Zi Wang +2
Dataset distillation (DD) aims to generate a compact yet informative dataset that achieves performance comparable to the original dataset, thereby reducing demands on storage and c…
Dataset Distillation via Vision-Language Category Prototype
Yawen Zou, Guang Li, Duo Su +3
Dataset distillation (DD) condenses large datasets into compact yet informative substitutes, preserving performance comparable to the original dataset while reducing storage, trans…