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[IROS 2021] Object-to-Scene: Learning to Transfer Object Knowledge to Indoor Scene Recognition.

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Object-to-Scene: Learning to Transfer Object Knowledge to Indoor Scene Recognition

This repository contains the source code (PyTorch) for our paper:

Object-to-Scene: Learning to Transfer Object Knowledge to Indoor Scene Recognition

Figure

Pre-trained model

  • The pre-trained model can be downloaded at Google drive.
  • Put the pre-trained model in the ckpt folder.

Introduction

  • The entrance file of test codes is main.py.
  • The main arguments and functions are in functions.py.

Citation

If you find the paper, code, or pre-trained models useful, please cite the following papers:

@InProceedings{Miao2021ots,
  author        = {Bo Miao and Liguang Zhou and Ajmal Mian and Tin Lun Lam and Yangsheng Xu},
  title         = {Object-to-Scene: Learning to Transfer Object Knowledge to Indoor Scene Recognition},
  booktitle     = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year          = {2021},
  organization  = {IEEE}
}

@InProceedings{Zhou21borm,
  author        = {Liguang Zhou and Cen Jun and Xingchao Wang and Zhenglong Sun and Tin Lun Lam and Yangsheng Xu},
  title         = {BORM: Bayesian Object Relation Model for Indoor Scene Recognition},
  booktitle     = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year          = {2021},
  organization  = {IEEE}
}

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