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Guoyuan Li

4 accepted papers

2026

Multi-State Consistency Visual Language Model Combine Wavelet Transform for Weakly Supervised Robot Visual Segmentation

ICRA 2026poster

Robotic visual segmentation is essential for enabling robots to operate in complex environments. Although supervised methods have achieved remarkable progress, their dependence on dense annotations hinders scalability. Weakly supervised semantic segmentation (WSSS) alleviates this issue but suffers …

Cited by 0Scholar
2022

A Camera-based Deep-Learning Solution for Visual Attention Zone Recognition in Maritime Navigational Operations

IROS 2022poster

The visual attention of navigators is imperative to understand the logic of navigation as well as the surveillance of navigators' status and operation. Current studies are implemented with the help of wearable eye-tracker glasses; yet, the high expenditure demanded by such equipment and service and…

Cited by 3SourceScholar
2021

Data-driven sea state estimation for vessels using multi-domain features from motion responses

ICRA 2021poster

Situation awareness is of great importance for autonomous ships. One key aspect is to estimate the sea state in a real-time manner. Considering the ship as a large wave buoy, the sea state can be estimated from motion responses without extra sensors installed. However, it is difficult to associate w…

Cited by 21SourceScholar
2019

Modeling and Analysis of Motion Data from Dynamically Positioned Vessels for Sea State Estimation

ICRA 2019poster

Developing a reliable model to identify the sea state is significant for the autonomous ship. This paper introduces a novel deep neural network model (SeaStateNet) to estimate the sea state based on the ship motion data from dynamically positioned vessels. The SeaStateNet mainly consists of three co…

Cited by 42SourceScholar