Xuejiao Wang — accepted AI-conference papers

2026

MOSA: MOTION-GUIDED SEMANTIC ALIGNMENT FOR DYNAMIC SCENE GRAPH GENERATION

ICASSP 2026poster

Dynamic Scene Graph Generation (DSGG) aims to structurally model objects and their dynamic interactions in video sequences for high-level semantic understanding. However, existing methods struggle with fine-grained relationship modeling, semantic representation utilization, and the ability to model…

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2024

CLIP-Driven Open-Vocabulary 3D Scene Graph Generation via Cross-Modality Contrastive Learning

Lianggangxu Chen, Xuejiao Wang, Jiale Lu, Shaohui Lin, Changbo Wang, Gaoqi He

CVPR 2024highlight

3D Scene Graph Generation (3DSGG) aims to classify objects and their predicates within 3D point cloud scenes. However current 3DSGG methods struggle with two main challenges. 1) The dependency on labor-intensive ground-truth annotations. 2) Closed-set classes training hampers the recognition of nove…

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