DarSwin-Unet: Distortion Aware Encoder-Decoder Architecture

Understand

Wide-angle fisheye images are becoming increasingly common for perception tasks in applications such as robotics, security, and mobility (e.g.

• drones, avionics).
• However, current models often either ignore the distortions in wide-angle images or are not suitable to perform pixel-level tasks.
• In this paper, we present an encoder-decoder model based on a radial transformer architecture that adapts to distortions in wide-angle lenses by leveraging the physical characteristics defined by the radial distortion profile.