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Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language Reasoning
Rui Li,
Tobias Fischer,
Mattia Segu,
Marc Pollefeys,
Luc Van Gool,
Federico Tombari
Computer Vision and Pattern Recognition (CVPR), 2024
project page
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arXiv
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code
A single-view 3D reconstruction method that disambiguates occluded scene geometry by utilizing Vision-Language semantics and spatial reasoning.
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GoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo
Jiang Wu*,
Rui Li*,
Haofei Xu,
Wenxun Zhao,
Yu Zhu,
Jinqiu Sun,
Yanning Zhang
(* equal contribution)
Computer Vision and Pattern Recognition (CVPR), 2024
project page
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arXiv
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code
A multi-view stereo approach with geometrically consistent matching cost aggregation using monocular normals.
1st place on Tanks and Temples (Advanced) leaderboard.
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Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes
Rui Li,
Dong Gong,
Wei Yin,
Hao Chen,
Yu Zhu,
Kaixuan Wang,
Xiaozhi Chen,
Jinqiu Sun,
Yanning Zhang
Computer Vision and Pattern Recognition (CVPR), 2023
project page
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video
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arXiv
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code
A multi-frame depth estimation approach that handles the dynamic areas by fusing monocular and multi-view cues in a mask-free manner.
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Learning depth via leveraging semantics: Self-supervised monocular depth estimation with both implicit and explicit semantic guidance
Rui Li,
Danna Xue,
Shaolin Su,
Xiantuo He,
Qing Mao,
Yu Zhu,
Jinqiu Sun,
Yanning Zhang
Pattern Recognition (PR), 2023
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code (coming soon)
A semantic-guided self-supervised depth estimation method that conducts implicit/explicit semantic guidance for high-quality and sharp depth.
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Enhancing Self-supervised Monocular Depth Estimation via Incorporating Robust Constraints
Rui Li,
Xiantuo He,
Yu Zhu,
Xianjun Li,
Jinqiu Sun,
Yanning Zhang
ACM International Conference on Multimedia (ACM MM), 2020
A self-supervised depth estimation method that incorporates robust constraints to improve photometric supervision.
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Academic Services
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- CVPR: 2023, 2024
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