DCCS-Det: Directional Context and Cross-Scale-Aware Detector for Infrared Small Target

• URL: http://arxiv.org/abs/2601.16428v1
• Date: Fri, 23 Jan 2026 03:53:59 GMT
• Title: DCCS-Det: Directional Context and Cross-Scale-Aware Detector for Infrared Small Target
• Authors: Shuying Li, Qiang Ma, San Zhang, Chuang Yang,
• Abstract summary: Infrared small target detection (IRSTD) is critical for applications like remote sensing and surveillance.<n>We propose DCCS-Det, a novel detector that incorporates a Dual-stream Saliency Enhancement (DSE) block and a Latent-aware Semantic Extraction and Aggregation (LaSEA) module.<n>Experiments show that DCCS-Det achieves state-of-the-art detection accuracy with competitive efficiency across multiple datasets.
• Score: 4.318503966844226
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Infrared small target detection (IRSTD) is critical for applications like remote sensing and surveillance, which aims to identify small, low-contrast targets against complex backgrounds. However, existing methods often struggle with inadequate joint modeling of local-global features (harming target-background discrimination) or feature redundancy and semantic dilution (degrading target representation quality). To tackle these issues, we propose DCCS-Det (Directional Context and Cross-Scale Aware Detector for Infrared Small Target), a novel detector that incorporates a Dual-stream Saliency Enhancement (DSE) block and a Latent-aware Semantic Extraction and Aggregation (LaSEA) module. The DSE block integrates localized perception with direction-aware context aggregation to help capture long-range spatial dependencies and local details. On this basis, the LaSEA module mitigates feature degradation via cross-scale feature extraction and random pooling sampling strategies, enhancing discriminative features and suppressing noise. Extensive experiments show that DCCS-Det achieves state-of-the-art detection accuracy with competitive efficiency across multiple datasets. Ablation studies further validate the contributions of DSE and LaSEA in improving target perception and feature representation under complex scenarios. \href{https://huggingface.co/InPeerReview/InfraredSmallTargetDetection-IRSTD.DCCS}{DCCS-Det Official Code is Available Here!}

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