CASENet: Deep Category-Aware Semantic Edge Detection

Understand

Boundary and edge cues are highly beneficial in improving a wide variety of vision tasks such as semantic segmentation, object recognition, stereo, and object proposal generation.

• Recently, the problem of edge detection has been revisited and significant progress has been made with deep learning.
• While classical edge detection is a challenging binary problem in itself, the category-aware semantic edge detection by nature is an even more challenging multi-label problem.
• We model the problem such that each edge pixel can be associated with more than one class as they appear in contours or junctions belonging to two or more semantic classes.