PlaneFormers: From Sparse View Planes to 3D Reconstruction

被引:14
作者
Agarwala, Samir [1 ]
Jin, Linyi [1 ]
Rockwell, Chris [1 ]
Fouhey, David F. [1 ]
机构
[1] Univ Michigan, Ann Arbor, MI USA
来源
COMPUTER VISION - ECCV 2022, PT III | 2022年 / 13663卷
关键词
D O I
10.1007/978-3-031-20062-5_12
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present an approach for the planar surface reconstruction of a scene from images with limited overlap. This reconstruction task is challenging since it requires jointly reasoning about single image 3D reconstruction, correspondence between images, and the relative camera pose between images. Past work has proposed optimization-based approaches. We introduce a simpler approach, the PlaneFormer, that uses a transformer applied to 3D-aware plane tokens to perform 3D reasoning. Our experiments show that our approach is substantially more effective than prior work, and that several 3D-specific design decisions are crucial for its success. Code is available at https://github.com/samiragarwala/PlaneFormers.
引用
收藏
页码:192 / 209
页数:18
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