MVLayoutNet:3D layout reconstruction with multi-view panoramas

• URL: http://arxiv.org/abs/2112.06133v1
• Date: Sun, 12 Dec 2021 03:04:32 GMT
• Title: MVLayoutNet:3D layout reconstruction with multi-view panoramas
• Authors: Zhihua Hu, Bo Duan, Yanfeng Zhang, Mingwei Sun, Jingwei Huang
• Abstract summary: MVNet is an end-to-end network for holistic 3D reconstruction from multi-view panoramas. We jointly train a layout module to produce an initial layout and a novel MVS module to obtain accurate layout geometry. Our method leads to coherent layout geometry that enables the reconstruction of an entire scene.
• Score: 12.981269280023469
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present MVLayoutNet, an end-to-end network for holistic 3D reconstruction from multi-view panoramas. Our core contribution is to seamlessly combine learned monocular layout estimation and multi-view stereo (MVS) for accurate layout reconstruction in both 3D and image space. We jointly train a layout module to produce an initial layout and a novel MVS module to obtain accurate layout geometry. Unlike standard MVSNet [33], our MVS module takes a newly-proposed layout cost volume, which aggregates multi-view costs at the same depth layer into corresponding layout elements. We additionally provide an attention-based scheme that guides the MVS module to focus on structural regions. Such a design considers both local pixel-level costs and global holistic information for better reconstruction. Experiments show that our method outperforms state-of-the-arts in terms of depth rmse by 21.7% and 20.6% on the 2D-3D-S [1] and ZInD [5] datasets. Finally, our method leads to coherent layout geometry that enables the reconstruction of an entire scene.

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