Author

Xiaoming Liu

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Preprint Aug 2026

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection

This work presents RefineAny3D, a vision-language model that corrects depth without ever predicting a numerical value, and delivers consistent gains across closed-set detectors, open-vocabulary detectors, and 3D auto-labeling tools, and generalizes to novel categories, scenes, and cameras without retraining.

Zhihao Zhang, Geng-Wei Zhang, Tianlong Chen et al. · 0 citations

Jul 2026

Geometric Distillation from Rectified Stereo: Leveraging Epipolar Cues for Monocular Depth

An Epipolar Distillation (EpiDistill), an approach utilizing Rectified Stereo Tokens, which enables the single-view prediction model to retain epipolar attention patterns and maintain geometric consistency without requiring multi-view inputs at inference, and significantly improves zero-shot metric depth estimation.

Jung-Hee Kim, Xiaoming Liu · arXiv.org · 0 citations