Monocular depth estimation has experienced significant progress on terrestrial images in
recent years thanks to deep learning advancements. But it remains inadequate for …

Many strategies have been proposed for underwater image enhancement. However, they
are often incompatible with underwater remotely operated vehicle platforms with low …

Autonomous navigation in the underwater environment is challenging due to limited
visibility, dynamic changes, and the lack of a cost-efficient, accurate localization system. We …

Underwater caves are challenging environments that are crucial for water resource
management, and for our understanding of hydro-geology and history. Mapping underwater …

Depth image-based rendering (DIBR) view synthesis is the most widely employed method in
real-time FVV research. Despite recent progress, most DIBR-based FVV synthesis …

In this work, we address the problem of real-time dense depth estimation from monocular
images for mobile underwater vehicles. We formulate a deep learning model that fuses …

By combining differentiable rendering with explicit point-based scene representations, 3D
Gaussian Splatting (3DGS) has demonstrated breakthrough 3D reconstruction capabilities …

Compared to the in-air case, underwater depth estimation has its own challenges. For
instance, acquiring high-quality training datasets with groundtruth poses difficulties due to …

Computer vision techniques have empowered underwater robots to effectively undertake a
multitude of tasks, including object tracking and path planning. However, underwater optical …

In the trending research of fusing Large Language Models (LLMs) and robotics, we aim to
pave the way for innovative development of AI systems that can enable Autonomous …