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20242026
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cs.CV2026

Semantic-Driven Scale and Spatial Selection for Efficient Cross-Modal Alignment in Referring Remote Sensing Image Segmentation

Kun Li, Shengxi Gui, Francesco Nex +1

Referring Remote Sensing Image Segmentation (RRSIS) seeks to localize and segment the target object or region specified by a natural language expression in a remote sensing image.…

cs.CV2026

Query-Guided Spatial-Temporal-Frequency Interaction for Music Audio-Visual Question Answering

Kun Li, Michael Ying Yang, Sami Sebastian Brandt

Audio--Visual Question Answering (AVQA) is a challenging multimodal task that requires jointly reasoning over audio, visual, and textual information in a given video to answer natu…

cs.CV2025

DVLO4D: Deep Visual-Lidar Odometry with Sparse Spatial-temporal Fusion

Mengmeng Liu, Michael Ying Yang, Jiuming Liu +5

Visual-LiDAR odometry is a critical component for autonomous system localization, yet achieving high accuracy and strong robustness remains a challenge. Traditional approaches comm…

cs.CV2025

Multimodal Rationales for Explainable Visual Question Answering

Kun Li, George Vosselman, Michael Ying Yang

Visual Question Answering (VQA) is a challenging task of predicting the answer to a question about the content of an image. Prior works directly evaluate the answering models by si…

cs.CV2025

Scale-wise Bidirectional Alignment Network for Referring Remote Sensing Image Segmentation

Kun Li, George Vosselman, Michael Ying Yang

The goal of referring remote sensing image segmentation (RRSIS) is to extract specific pixel-level regions within an aerial image via a natural language expression. Recent advancem…

cs.CV2024

Planner3D: LLM-enhanced graph prior meets 3D indoor scene explicit regularization

Yao Wei, Martin Renqiang Min, George Vosselman +2

Compositional 3D scene synthesis has diverse applications across a spectrum of industries such as robotics, films, and video games, as it closely mirrors the complexity of real-wor…