iMat Product 2019
As online shopping and retail AI become ubiquitous in our daily life, it is imperative for computer vision systems to automatically and accurately recognize products based on images at the stock keeping unit (SKU) level. However, this still remains a challenging problem since there is a large number of SKU-level categories, many of which are fine-grained, with very subtle differences that cannot be easily distinguished. At the same time, images of the same product or SKU can often look different under different conditions (e.g., user generated content v.s. professional generated content).
By providing a large scale dataset and hosting a competition, Malong Technologies and FGVC workshop organizers encourage computer vision researchers to develop novel algorithms to tackle this interesting problem. Individuals/teams with top submissions may be invited to present their work at the FGVC6 workshop at CVPR 2019 and share a $3,000 cash prizes.
Xintong Han, Malong Technologies
Sheng Guo, Malong Technologies
Lingshu Kong, Malong Technologies
Weilin Huang, Malong Technologies
Matt Scott, Malong Technologies