IROS 2019 Lifelong Robotic Vision Challenge -- Lifelong Object Recognition Report

• DOI: 10.48550/arxiv.2004.14774
• Publication Date: 2020-01-01
• Authors: She, Qi; Feng, Fan; Liu, Qi; Chan, Rosa H. M.; Hao, Xinyue; Lan, Chuanlin; Yang, Qihan; Lomonaco, Vincenzo; Parisi, German I.; Bae, Heechul; Brophy, Eoin; Chen, Baoquan; Graffieti, Gabriele; Goel, Vidit; Han, Hyonyoung; Kanagarajah, Sath...; Kumar, Somesh; Lam, Siew-Kei; Lam, Tin Lun; Ma, Liang; Maltoni, Davide; Pellegrini, Lorenzo; Piyasena, Duvindu; Pu, Shiliang; Sheet, Debdoot; Song, Soonyong; Son, Youngsung; Wang, Zhengwei; Ward, Tomas E.; Wu, Jianwen; Wu, Meiqing; Xie, Di; Xu, Yangsheng; Yang, Lin; Zhong, Qiaoyong; Zhou, Liguang
• Keywords: FOS: Computer and information sciences; Computer Science - Machine Learning; Computer Vision and Pattern Recognition (cs.CV); Image and Video Processing (eess.IV); Computer Science - Computer Vision and Pattern Recognition; Machine Learning (stat.ML); 02 engineering and technology; Electrical Engineering and Systems Science - Image and Video Processing; Machine Learning (cs.LG); Computer Science - Robotics; Statistics - Machine Learning; 0202 electrical engineering, electronic engineering, information engineering; FOS: Electrical engineering, electronic engineering, information engineering; Robotics (cs.RO)

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/".<br/>9 pages, 11 figures, 3 tables, accepted into IEEE Robotics and Automation Magazine. arXiv admin note: text overlap with arXiv:1911.06487<br/>