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A Style-Based Profiling Framework for Quantifying the Synthetic-to-Real Gap in Autonomous Driving Datasets
Dingyi Yao, Xinyao Han, Ruibo Ming +5
Ensuring the reliability of autonomous driving perception systems requires extensive environment-based testing, yet real-world execution is often impractical. Synthetic datasets ha…
OMeGa: Joint Optimization of Explicit Meshes and Gaussian Splats for Robust Scene-Level Surface Reconstruction
Yuhang Cao, Haojun Yan, Danya Yao
Neural rendering with Gaussian splatting has advanced novel view synthesis, and most methods reconstruct surfaces via post-hoc mesh extraction. However, existing methods suffer fro…
Synthetic Dataset Evaluation Based on Generalized Cross Validation
Zhihang Song, Dingyi Yao, Ruibo Ming +3
With the rapid advancement of synthetic dataset generation techniques, evaluating the quality of synthetic data has become a critical research focus. Robust evaluation not only dri…
A re-calibration method for object detection with multi-modal alignment bias in autonomous driving
Zhihang Song, Dingyi Yao, Ruibo Ming +3
Multi-modal object detection in autonomous driving has achieved great breakthroughs due to the usage of fusing complementary information from different sensors. The calibration in…