most citedLearning A Robust RGB-Thermal Detector for Extreme Modality Imbalance

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.CV2026

Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding

Chang Liu, Henghui Ding, Nikhila Ravi +40

This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge, hosted at CVPR 2026, whi…

cs.CV2026

AgentRVOS for MeViS-Text Track of 5th PVUW Challenge: 3rd Method

Deshui Miao, Chao Yang, Chao Tian +4

This report describes a Ref-VOS pipeline centered on Sa2VA and organized with explicit agent roles. The key idea is that Sa2VA should provide the first dense semantic hypothesis, w…

cs.CV2026

Fusing in 3D: Free-Viewpoint Fusion Rendering with a 3D Infrared-Visible Scene Representation

Chao Yang, Deshui Miao, Chao Tian +3

Infrared-visible image fusion aims to integrate infrared and visible information into a single fused image. Existing 2D fusion methods focus on fusing images from fixed camera view…

cs.CV2026

Modality-Decoupled RGB-Thermal Object Detector via Query Fusion

Chao Tian, Zikun Zhou, Chao Yang +3

The advantage of RGB-Thermal (RGB-T) detection lies in its ability to perform modality fusion and integrate cross-modality complementary information, enabling robust detection unde…

cs.CV20251 cited

Learning A Robust RGB-Thermal Detector for Extreme Modality Imbalance

Chao Tian, Chao Yang, Guoqing Zhu +2

RGB-Thermal (RGB-T) object detection utilizes thermal infrared (TIR) images to complement RGB data, improving robustness in challenging conditions. Traditional RGB-T detectors assu…