activity
20212026
most citedFEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation

6 citations · 8 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2026

CALM-AH: An ABAW11-Calibrated Multimodal Ensemble with Reliability-Gated Multi-Expert Consensus for Video-Level Ambivalence and Hesitancy Recognition

Wenzhuo Sun, Mingjian Liang, Richard Attfield +3

Ambivalence and hesitancy (A/H) are subtle behavioural states that may be expressed through language, voice, facial activity, and other non-verbal cues. The ABAW11 A/H Video Recogn…

cs.CV2026

RTFDNet: Fusion-Decoupling for Robust RGB-T Segmentation

Kunyu Tan, Mingjian Liang

RGB-Thermal (RGB-T) semantic segmentation is essential for robotic systems operating in low-light or dark environments. However, traditional approaches often overemphasize modality…

cs.CV2023★ 1 cited

Explicit Attention-Enhanced Fusion for RGB-Thermal Perception Tasks

Mingjian Liang, Junjie Hu, Chenyu Bao +3

Recently, RGB-Thermal based perception has shown significant advances. Thermal information provides useful clues when visual cameras suffer from poor lighting conditions, such as l…

cs.CV2021★ 1 cited

Abnormal Occupancy Grid Map Recognition using Attention Network

Fuqin Deng, Hua Feng, Mingjian Liang +6

The occupancy grid map is a critical component of autonomous positioning and navigation in the mobile robotic system, as many other systems' performance depends heavily on it. To g…

cs.CV2021★ 6 cited

FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation

Fuqin Deng, Hua Feng, Mingjian Liang +7

The RGB-Thermal (RGB-T) information for semantic segmentation has been extensively explored in recent years. However, most existing RGB-T semantic segmentation usually compromises…