LEARNING TO FIND BOUNDARIES WITH BOUNDARY ATTENTION

Summary from the TLDR AI newsletter

Finding contours and boundaries in images is a classic computer vision problem. However, when introducing noise, quality shifts, or out-of-distribution examples, many existing methods fail to perform well. This new learned method performs extremely well on sensor readings and is only 207k parameters. It uses a two-stage training process and greatly improves state of the art.