Action-Aligned Retrieval with Pairwise Multimodal Reranking for Text-Based Person Anomaly Search
Text-based person anomaly search requires distinguishing individuals based on fine-grained, context-dependent behaviors rather than mere appearance. Existing methods struggle to capture these context-conditioned actions, frequently relying on isolated skeletal geometry, discarding raw query details during reformulation, or utilizing absolute pointwise scoring for multimodal verification. To address these limitations, we propose \textbf{ActPair}, a unified three-stage coarse-to-fine framework that combines action-aligned retrieval with pairwise multimodal reranking to bridge the pose-semantic g
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- FuzzySimilar title/name (fuzzy) · 84%liguodongiot/llm-action →
“Fuzzy title match (0.92): “Action-Aligned Retrieval with Pairwise Multimodal Reranking ” ≈ “liguodongiot/llm-action””
- FuzzyOverlapping authors or contributors · 62%open-webui/open-webui →
“Shared author/contributor keys: nguyen”
- FuzzyOverlapping authors or contributors · 62%ultralytics/yolov5 →
“Shared author/contributor keys: tran”
- LinkedLinked via arxiv author · 85%Thanh-Khoi Nguyen →
“Action-Aligned Retrieval with Pairwise Multimodal Reranking for Text-Based Person Anomaly Search”
- LinkedLinked via arxiv author · 85%Thanh-Nhan Vo →
“Action-Aligned Retrieval with Pairwise Multimodal Reranking for Text-Based Person Anomaly Search”
- LinkedLinked via arxiv author · 85%Trong-Thuan Nguyen →
“Action-Aligned Retrieval with Pairwise Multimodal Reranking for Text-Based Person Anomaly Search”
- LinkedLinked via arxiv author · 85%Minh-Triet Tran →
“Action-Aligned Retrieval with Pairwise Multimodal Reranking for Text-Based Person Anomaly Search”