The progress in maritime obstacle detection is hindered by the lack of a diverse dataset that
adequately captures the complexity of general maritime environments. We present the first …

Certain fields present significant challenges when attempting to train complex Deep
Learning architectures, particularly when the available datasets are limited and imbalanced …

Deep learning-based visual perception of an unmanned surface vehicle (USV) essentially
benefits from informative images. It is unfortunately short of available datasets of marine …

Re-identification (ReID) in multi-object tracking (MOT) for UAVs in maritime computer vision
has been challenging for several reasons. More specifically, short-term re-identification …

The increasing popularity of compact and inexpensive cameras, eg dash cameras, body
cameras, and cameras equipped on robots, has sparked a growing interest in detecting …

This paper introduces a novel approach to video object detection detection and tracking on
Unmanned Aerial Vehicles (UAVs). By incorporating metadata, the proposed approach …

In recent years, we've witnessed the remarkable growth of computer vision applications in
both maritime and freshwater domains. These technologies have played pivotal roles in …

Abstract The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 continues to
emphasize maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned …

Contrastive learning methods that bridge textual descriptions and images, such as
Contrastive Language-Image Pre-training (CLIP), have demonstrated remarkable …

In recent years, the significance of unmanned surface vehicles (USVs) has grown
substantially across a wide range of applications. Monocular cameras, as the most common …