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New framework bridges pose-semantic gap for text-based person anomaly search

Researchers have developed a new framework called the Structure-Semantic Decoupled Cascade (SSDC) to improve text-based person anomaly search in surveillance footage. This method addresses the Pose-Semantic Gap, where different actions can have similar skeletal structures, by first using a lightweight model for coarse retrieval based on skeletal similarity. It then employs a multi-agent semantic verification module, comprising a Detective, Analyst, and Writer, to refine the search results by synthesizing semantic captions and fusing them with structural information. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Introduces a novel framework for efficient and accurate anomaly detection in surveillance, potentially improving security systems.

RANK_REASON This is a research paper introducing a new framework for anomaly search in computer vision.

Read on arXiv cs.CV →

COVERAGE [1]

  1. arXiv cs.CV TIER_1 · Zequn Xie, Guijin Luo, Chuxin Wang, Sihang Cai, Tao Jin, Zhou Zhao, Yixuan Tang ·

    Bridging the Pose-Semantic Gap: A Cascade Framework for Text-Based Person Anomaly Search

    arXiv:2604.23282v1 Announce Type: new Abstract: Text-based person anomaly search retrieves specific behavioral events from surveillance archives using natural-language queries. Although recent pose-aware methods align geometric structures well, they face a fundamental Pose-Semant…