Semantic Scene Completion via Integrating Instances and Scene in-the-Loop

@article{Cai2021SemanticSC,
  title={Semantic Scene Completion via Integrating Instances and Scene in-the-Loop},
  author={Yingjie Cai and Xuesong Chen and Chao Zhang and Kwan-Yee Lin and Xiaogang Wang and Hongsheng Li},
  journal={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021},
  pages={324-333}
}
Semantic Scene Completion aims at reconstructing a complete 3D scene with precise voxel-wise semantics from a single-view depth or RGBD image. It is a crucial but challenging problem for indoor scene understanding. In this work, we present a novel framework named Scene-Instance-Scene Network (SISNet), which takes advantages of both in-stance and scene level semantic information. Our method is capable of inferring fine-grained shape details as well as nearby objects whose semantic categories are… 

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