2 citations · 2 across the 6 of their papers we have counts for
6 papers
SGFormer++: Semantic Graph Transformer for Incremental 3D Scene Graph Generation
Mengshi Qi, Changsheng Lv, Zijian Fu +2
In this paper, we propose SGFormer++, a novel Semantic Graph Transformer for 3D scene graph generation (SGG), which aims to parse point cloud scenes into semantic structural graphs…
Multi-Modal Scene Graph with Kolmogorov-Arnold Experts for Audio-Visual Question Answering
Zijian Fu, Changsheng Lv, Xianlin Zhang +2
In this paper, we propose a novel Multi-Modal Scene Graph with Kolmogorov-Arnold Expert Network for Audio-Visual Question Answering (SHRIKE). The task aims to mimic human reasoning…
Robo-SGG: Exploiting Layout-Oriented Normalization and Restitution Can Improve Robust Scene Graph Generation
Changsheng Lv, Zijian Fu, Mengshi Qi
In this paper, we propose Robo-SGG, a plug-and-play module for robust scene graph generation (SGG). Unlike standard SGG, the robust scene graph generation aims to perform inference…
Robust Disentangled Counterfactual Learning for Physical Audiovisual Commonsense Reasoning
Mengshi Qi, Changsheng Lv, Huadong Ma
In this paper, we propose a new Robust Disentangled Counterfactual Learning (RDCL) approach for physical audiovisual commonsense reasoning. The task aims to infer objects' physics…
T2SG: Traffic Topology Scene Graph for Topology Reasoning in Autonomous Driving
Changsheng Lv, Mengshi Qi, Liang Liu +1
Understanding the traffic scenes and then generating high-definition (HD) maps present significant challenges in autonomous driving. In this paper, we defined a novel Traffic Topol…
Disentangled Counterfactual Learning for Physical Audiovisual Commonsense Reasoning
Changsheng Lv, Shuai Zhang, Yapeng Tian +2
In this paper, we propose a Disentangled Counterfactual Learning~(DCL) approach for physical audiovisual commonsense reasoning. The task aims to infer objects' physics commonsense…