Selected work

Representative Papers

RECAST: From Log Replay to Closed-Loop Driving Simulation with View-Complete Actors

Sep 25, 2026

This study addresses the challenge of viewpoint-induced rendering artifacts and unreliable observations for dynamic actors in closed-loop driving simulation. To this end, it proposes a two-stage model adaptation strategy based on 3D Gaussian Splatting. By leveraging image-to-3D priors, the method generates view-consistent complete actors from single frames and registers them into the scene, thereby enabling planner-in-the-loop closed-loop interactive simulation. Furthermore, the RECAR dataset is constructed to facilitate controllable evaluation beyond logged trajectories. Experimental results demonstrate that the proposed approach significantly reduces the Fréchet distance while improving the CLIP score. In closed-loop evaluations, the method achieves a collision-free rate of 63% and increases the average Time-to-Collision (TTC) to 2.15 seconds, indicating substantially enhanced safety and realism in autonomous driving simulation.

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Boundary-Aligned Contribution Routing for Robust Optical--SAR Object Detection

Aug 15, 2026

This study addresses the negative transfer issue arising from imperfect modal correspondence in optical-SAR fusion detection by proposing a Boundary-Aligned Contribution Routing mechanism. Leveraging feature-level and dual-statistic semantic routers, this method dynamically modulates modal contributions prior to feature mixing without requiring additional utility supervision, thereby effectively suppressing negative transfer. Experimental results demonstrate that the proposed mechanism significantly enhances fusion robustness, improving mean Average Precision (mAP) by 0.5–5.9 points under full-input conditions and 7.6–41.6 points in missing-modality scenarios. Furthermore, it reduces the negative transfer rate by up to 12.7%, successfully mitigating performance degradation challenges inherent in heterogeneous multimodal fusion tasks.

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Recent publications

Latest Papers

RECAST: From Log Replay to Closed-Loop Driving Simulation with View-Complete Actors

Sep 25, 2026

This study addresses the challenge of viewpoint-induced rendering artifacts and unreliable observations for dynamic actors in closed-loop driving simulation. To this end, it proposes a two-stage model adaptation strategy based on 3D Gaussian Splatting. By leveraging image-to-3D priors, the method generates view-consistent complete actors from single frames and registers them into the scene, thereby enabling planner-in-the-loop closed-loop interactive simulation. Furthermore, the RECAR dataset is constructed to facilitate controllable evaluation beyond logged trajectories. Experimental results demonstrate that the proposed approach significantly reduces the Fréchet distance while improving the CLIP score. In closed-loop evaluations, the method achieves a collision-free rate of 63% and increases the average Time-to-Collision (TTC) to 2.15 seconds, indicating substantially enhanced safety and realism in autonomous driving simulation.

0 citationsRead paper

Boundary-Aligned Contribution Routing for Robust Optical--SAR Object Detection

Aug 15, 2026

This study addresses the negative transfer issue arising from imperfect modal correspondence in optical-SAR fusion detection by proposing a Boundary-Aligned Contribution Routing mechanism. Leveraging feature-level and dual-statistic semantic routers, this method dynamically modulates modal contributions prior to feature mixing without requiring additional utility supervision, thereby effectively suppressing negative transfer. Experimental results demonstrate that the proposed mechanism significantly enhances fusion robustness, improving mean Average Precision (mAP) by 0.5–5.9 points under full-input conditions and 7.6–41.6 points in missing-modality scenarios. Furthermore, it reduces the negative transfer rate by up to 12.7%, successfully mitigating performance degradation challenges inherent in heterogeneous multimodal fusion tasks.

0 citationsRead paper