Low-Power Image Recognition Challenge (LPIRC 2018)
Low-Power Image Recognition Challenge (LPIRC) 2018
Salt Lake City, Utah, June 18, 2018
The 4th IEEE International Low-Power Image Recognition Challenge (LPIRC) will be held in Salt Lake City, Utah, co-located with International Conference on Computer Vision and Pattern Recognition (CVPR 2018). This year, team contributions are being encouraged for 3 different tracks:
Track 1: Teams submit their models in TfLite format before CVPR for image classification. This track focuses on accuracy and execution time on a fixed compute platform.
Track 2: Teams submit their programs before CVPR for object detection. The organizers will execute the programs on Nvidia TX2 and measure the accuracy and energy consumption.
Track 3: This is the same track as 2017. Participants bring their systems to an on-site competition for object detection. There is no restriction on the hardware (except Nvidia TX2) or software. This track is the same as the previous years.
More details about the tracks will be announced on this website soon.
Please download training data at http://image-net.org/challenges/LSVRC/2013/
The registration site is now open: http://lpirc.ecn.purdue.edu/
Prizes in each track: $2,000 for first prize, $1,000 for second prize, $500 for third prize.
Submission for Tracks 1 and 2 are open between May 25 and June 10. Track 3 is on-site and participants need to bring their own systems.
Financial Sponsors: IEEE Rebooting Computing, Google, and Facebook.
Technical Sponsors: Google and Facebook.
For inquiries, please contact email@example.com.
Many mobile systems (smartphones, electronic glass, autonomous robots) can capture images. These systems use batteries and energy conservation is essential. This challenge aims to discover the best technology in both image recognition and energy conservation. Winners will be evaluated based on both high recognition accuracy and low power usage.
Image recognition involves many tasks. This challenge focuses on object detection, a basic routine in many recognition approaches. The following two examples illustrate the task. In the first example, there are two objects: a bird and a frog. In the second example, there are several objects: cars, persons, motorcycle, and a helmet. The training and validation data for LPIRC comes from the ImageNet Large Scale Visual Recognition Challenge detection competition. The test data will be specific to LPIRC.
Retrospect and Prospect of LPIRC (PDF, 2 MB), presented at DATE (Design and Test in Europe), March 2018
Three Years of LPIRC (PDF, 3 MB), presented at ASPLOS, March 2018
Previous Competition Websites: