arXiv:2608.14207v2 Announce Type: replace-cross Abstract: Perception from a single unmanned surface vehicle (USV) is limited by sensing range, field of view, and occlusions caused by islands, port in...
arXiv:2606. 30049v1 Announce Type: cross Abstract: Visibility distance is critical to maritime navigational safety because it determines the effective observation range of shipborne and shore-based monitoring systems.
MIC-BEV is a Transformer-based bird's-eye-view perception framework designed for infrastructure-based multi-camera 3D object detection. It supports a variable number of heterogeneous cameras and employs a graph-enhanced fusion module to adaptively integrate multi-view image features by modeling geometric relationships between cameras and the BEV grid. The authors introduce the M2I synthetic dataset and evaluate MIC-BEV on both M2I and the real-world RoScenes dataset, demonstrating strong detection performance, improved robustness under challenging conditions, and practical feasibility for deployment.
arXiv:2608. 07018v1 Announce Type: cross Abstract: Horizon detection in images of ice-covered waters is a challenging problem for maritime navigation due to low contrast between water and sky, cluttered ice structures, and varying illumination conditions.
arXiv:2603. 08457v2 Announce Type: replace-cross Abstract: Robust single-vessel tracking from fixed coastal platforms is hindered by modality-specific degradations: cameras suffer from illumination and visual clutter, while LiDAR performance drops with range and intermittent returns.
arXiv:2602. 19349v2 Announce Type: replace-cross Abstract: LiDAR-camera fusion enhances 3D panoptic segmentation by leveraging camera images to complement sparse LiDAR scans, but it also introduces a critical failure mode.
arXiv:2609.37003v1 Announce Type: new Abstract: Vessel perception from space is crucial for a wide range of maritime applications, from traffic monitoring to environmental protection. However, most e...
Vessel perception from space is crucial for a wide range of maritime applications, from traffic monitoring to environmental protection. However, most existing datasets predominantly focus on general o...
This paper presents a novel strategy for UAV detection through visible (RGB) and infrared (IR) fusion, in order to improve accuracy and precision in harsh environments and weather conditions. In this...
arXiv:2510. 04876v3 Announce Type: replace-cross Abstract: Benthic habitat mapping is fundamental for understanding marine ecosystems, guiding conservation efforts, and supporting sustainable resource management.
arXiv:2506. 22174v3 Announce Type: replace-cross Abstract: The transport industry has recently shown significant interest in unmanned surface vehicles (USVs), specifically for port and inland waterway transport.
This study compares two fusion strategies for UAV detection using RGB and infrared imagery: early (image-level) fusion and late (decision-level) fusion. Extensive testing in varied lighting, backgrounds, distances, altitudes, and zoom levels shows that early fusion yields higher raw performance by integrating thermal data from the start, while late fusion offers a flexible workflow useful when sensors or frames are misaligned. The paper discusses both strengths and weaknesses of each approach and provides practical implementation recommendations.