Corpus ID: 29476958

Self corrective Perturbations for Semantic Segmentation and Classification

  title={Self corrective Perturbations for Semantic Segmentation and Classification},
  author={S. Sankaranarayanan and Arpit Jain and S. Lim},
  journal={arXiv: Computer Vision and Pattern Recognition},
Convolutional Neural Networks have been a subject of great importance over the past decade and great strides have been made in their utility for producing state of the art performance in many computer vision problems. However, the behavior of deep networks is yet to be fully understood and is still an active area of research. In this work, we present an intriguing behavior: pre-trained CNNs can be made to improve their predictions by structurally perturbing the input. We observe that these… Expand


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