  With the advancements of various autonomous car projects aiming to achieve
SAE Level 5, real-time detection of traffic signs in real-life scenarios has
become a highly relevant problem for the industry. Even though a great progress
has been achieved in this field, there is still no clear consensus on what the
state-of-the-art in this field is.
  Moreover, it is important to develop and test systems in various regions and
conditions. This is why the "Ice Vision" competition has focused on the
detection of Russian traffic signs in winter conditions. The IceVisionSet
dataset used for this competition features real-world collection of lossless
frame sequences with traffic sign annotations. The sequences were collected in
varying conditions, including: different weather, camera exposure, illumination
and moving speeds.
  In this work we describe the competition and present the solutions of the 3
top teams.
