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Thinking Ahead: Foresight Intelligence in MLLMs and World Model
Zhantao Gong, Liaoyuan Fan, Qing Guo +3
In this work, we define Foresight Intelligence as the capability to anticipate and interpret future events-an ability essential for applications such as autonomous driving, yet lar…
Exploiting Vision Language Model for Training-Free 3D Point Cloud OOD Detection via Graph Score Propagation
Tiankai Chen, Yushu Li, Adam Goodge +4
Out-of-distribution (OOD) detection in 3D point cloud data remains a challenge, particularly in applications where safe and robust perception is critical. While existing OOD detect…
SODA: Out-of-Distribution Detection in Domain-Shifted Point Clouds via Neighborhood Propagation
Adam Goodge, Xun Xu, Bryan Hooi +4
As point cloud data increases in prevalence in a variety of applications, the ability to detect out-of-distribution (OOD) point cloud objects becomes critical for ensuring model sa…
Multi-View Industrial Anomaly Detection with Epipolar Constrained Cross-View Fusion
Yifan Liu, Xun Xu, Shijie Li +2
Multi-camera systems provide richer contextual information for industrial anomaly detection. However, traditional methods process each view independently, disregarding the compleme…
Global-Aware Monocular Semantic Scene Completion with State Space Models
Shijie Li, Zhongyao Cheng, Rong Li +4
Monocular Semantic Scene Completion (MonoSSC) reconstructs and interprets 3D environments from a single image, enabling diverse real-world applications. However, existing methods a…
Future-Aware Interaction Network For Motion Forecasting
Shijie Li, Xun Xu, Si Yong Yeo +1
Motion forecasting is a crucial component of autonomous driving systems, enabling the generation of accurate and smooth future trajectories to ensure safe navigation to the destina…