Bosen Hou — accepted AI-conference papers

2026

SABER: Spatially Consistent 3D Universal Adversarial Objects for BEV Detectors

Aixuan Li, Mochu Xiang, Bosen Hou, Zhexiong Wan, Jing Zhang, Yuchao Dai

CVPR 2026

Adversarial robustness of BEV 3D object detectors is critical for autonomous driving (AD). Existing invasive attacks require altering the target vehicle itself (e.g. attaching patches), making them unrealistic and impractical for real-world evaluation. While non-invasive attacks that place adversari

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2026

SPE-MVS: Spatial Position Encoding Enhanced Multi-View Stereo with Monocular Depth Priors

Shaoqian Wang, Jiadai Sun, Bosen Hou, Qiang Wang, Bin Fan, Bo Li +2

CVPR 2026

Learning-based Multi-View Stereo (MVS) methods have become the mainstream in the field, relying on the construction of cost Learning-based Multi-View Stereo (MVS) methods have become the mainstream in the field, relying on the construction of cost volumes through multi-view feature similarity comput

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