• Corpus ID: 235358207

Transformed ROIs for Capturing Visual Transformations in Videos

@article{Rai2021TransformedRF,
  title={Transformed ROIs for Capturing Visual Transformations in Videos},
  author={Abhinav Rai and Fadime Sener and Angela Yao},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.03162}
}
Modeling the visual changes that an action brings to a scene is critical for video understanding. Currently, CNNs process one local neighbourhood at a time, so contextual relationships over longer ranges, while still learnable, are indirect. We present TROI, a plug-and-play module for CNNs to reason between mid-level feature representations that are otherwise separated in space and time. The module relates localized visual entities such as hands and interacting objects and transforms their… 

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