  This report summarizes IROS 2019-Lifelong Robotic Vision Competition
(Lifelong Object Recognition Challenge) with methods and results from the top
$8$ finalists (out of over~$150$ teams). The competition dataset (L)ifel(O)ng
(R)obotic V(IS)ion (OpenLORIS) - Object Recognition (OpenLORIS-object) is
designed for driving lifelong/continual learning research and application in
robotic vision domain, with everyday objects in home, office, campus, and mall
scenarios. The dataset explicitly quantifies the variants of illumination,
object occlusion, object size, camera-object distance/angles, and clutter
information. Rules are designed to quantify the learning capability of the
robotic vision system when faced with the objects appearing in the dynamic
environments in the contest. Individual reports, dataset information, rules,
and released source code can be found at the project homepage:
"https://lifelong-robotic-vision.github.io/competition/".
