• Corpus ID: 246442335

Interactron: Embodied Adaptive Object Detection

@article{Kotar2022InteractronEA,
  title={Interactron: Embodied Adaptive Object Detection},
  author={Klemen Kotar and Roozbeh Mottaghi},
  journal={ArXiv},
  year={2022},
  volume={abs/2202.00660}
}
Over the years various methods have been proposed for the problem of object detection. Recently, we have wit-nessed great strides in this domain owing to the emergence of powerful deep neural networks. However, there are typically two main assumptions common among these approaches. First, the model is trained on a fixed training set and is evaluated on a pre-recorded test set. Second, the model is kept frozen after the training phase, so no further updates are performed after the training is… 
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