High-for-Low and Low-for-High: Efficient Boundary Detection from Deep Object Features and its Applications to High-Level Vision

Understand

Most of the current boundary detection systems rely exclusively on low-level features, such as color and texture.

• However, perception studies suggest that humans employ object-level reasoning when judging if a particular pixel is a boundary.
• Inspired by this observation, in this work we show how to predict boundaries by exploiting object-level features from a pretrained object-classification network.
• Our method can be viewed as a "High-for-Low" approach where high-level object features inform the low-level boundary detection process.