The dataset contains three different folders:

  1. ATEL1Frames: It contains the frames of a video captured using a surveillance camera in the natural environment using multiple subjects
  2. AT_Face_Coordinates: It contains the face coordinates of the subjects at a frame level. Frame no. is the index of the face location in the coordinate files.
  3. HR Gallery: It contains the high-resolution gallery images of each subject who participated in the data collection. 4 images of each participant are acquired for gallery-based face matching.

Each directory contains a test, Val, and train folders.

In both training and validation sets: the original directory refers to the clean images and pt_xxxxx refers to the turbulence-affected images. In the test set original and two different sets of turbulence images (namely XY and XY directories) are provided. The participants need to submit a score matrix corresponding to each set along with a max 2-page write-up describing their approach and performance on the training/Val set.



  1. The participants need to use only the training set for developing the network. Use of test sets is strictly prohibited.
  2. Avoid any form of cheating including manual annotations on the test. It is advised to develop ethical solutions.
  3. Participants are free to use any face cropping algorithm if they want to.
  4. Matching will only be performed using the HR gallery images provided.
  5. Participants need to submit the score matrix on the test set. For instance, if the test contains images of "N" subjects and contains M frames, then the score matrix will have the scores: (MxK)*(Nx4). Where 4 represents the number of gallery images of each N subject and k represents the number of subjects present in one frame.
  6. The evaluation will be performed both at the frame and video level. The score of videos will be calculated as the average scores of all the frames in that video.
  7. To obtain the dataset, participants need to sign the license agreement of the DroneSURF dataset ( Once the agreement is approved we will provide the link to the dataset of this challenge.

Data Link: Coming Soon.

Deadline: Score matrix submission: 05/15/2022