A Solution to Product detection in Densely Packed Scenes

Code

• github.com/Media-Smart/SKU110K-DenseDet
  pytorch★ 111
• github.com/TanyaChutani/SSD-Tensorflow2.0
  tf★ 33

Abstract

This work is a solution to densely packed scenes dataset SKU-110k. Our work is modified from Cascade R-CNN. To solve the problem, we proposed a random crop strategy to ensure both the sampling rate and input scale is relatively sufficient as a contrast to the regular random crop. And we adopted some of trick and optimized the hyper-parameters. To grasp the essential feature of the densely packed scenes, we analysis the stages of a detector and investigate the bottleneck which limits the performance. As a result, our method obtains 58.7 mAP on test set of SKU-110k.

Tasks

Reproductions