Mono Depth Perception

Estimate Depth in Aerial Images From Downward-Facing Drone Images

Welcome to the Mono Depth Perception Challenge!

This is a competition run by AIcrowd & Amazon Prime Air, focusing on images of a single downward camera to estimate the scene’s depth and perform semantic segmentation. As a result, these two tasks can help the development of safe and reliable autonomous control systems for aircraft.

The objective of this challenge is to encourage the advancement of completely self-governing Unmanned Aircraft Systems (UAS) through the introduction of a fresh dataset of drone imagery. The dataset is intended to serve as a benchmark for semantic segmentation and mono-depth perception and contains realistic backyard scenarios with diverse content, captured at various Above Ground Level (AGL) ranges.

The two fundamental components of this project pertaining to computer vision are semantic segmentation and depth perception. Through this challenge, the Computer Vision community is encouraged to innovate and enhance the cutting-edge perception tasks related to drone images. The focus in this particular task is on the mono-depth estimation.


  • Challenge Launch: 22nd December 2022
  • Challenge End: 28th April 2023
  • Winner Announcement: 30th June 2023


  • The Top scoring submission will receive $15,000 USD
  • The Second best submission will receive $7,500 USD
  • The Third place submission will receive $1,250 USD
  • The Most “Creative” solution submitted to the whole competition, as determined by the Sponsor’s sole discretion, will receive $2,500 USD.

Sponsored by Saturn Cloud

The dataset is hosted by Saturn Cloud, which will be available for download. Each participant can use the Saturn Cloud computing environment, which provides 100 free hours of compute per participant, and a Python environment. Message Saturn Cloud support and say, "I'm competing in the Mono Depth Perception challenge." You'll be upgraded from the standard free tier to 100 hours of compute! Click the link below to get started with the competition.