Web: http://arxiv.org/abs/2209.06395

Sept. 15, 2022, 1:13 a.m. | Haobo Jiang, Kaihao Lan, Le Hui, Guangyu Li, Jin Xie, Jian Yang

cs.CV updates on arXiv.org arxiv.org

Learning robust feature matching between the template and search area is
crucial for 3D Siamese tracking. The core of Siamese feature matching is how to
assign high feature similarity on the corresponding points between the template
and search area for precise object localization. In this paper, we propose a
novel point cloud registration-driven Siamese tracking framework, with the
intuition that spatially aligned corresponding points (via 3D registration)
tend to achieve consistent feature representations. Specifically, our method
consists of two modules, …

arxiv cloud feature registration tracking

More from arxiv.org / cs.CV updates on arXiv.org

Machine Learning Product Manager (Canada, Remote)

@ FreshBooks | Canada

Data Engineer

@ Amazon.com | Irvine, California, USA

Senior Autonomy Behavior II, Performance Assessment Engineer

@ Cruise LLC | San Francisco, CA

Senior Data Analytics Engineer

@ Intercom | Dublin, Ireland

Data Analyst Intern

@ ADDX | Singapore

Data Science Analyst - Consumer

@ Yelp | London, England, United Kingdom

Senior Data Analyst - Python+Hadoop

@ Capco | India - Bengaluru

DevOps Engineer, Data Team

@ SingleStore | Hyderabad, India

Software Engineer (Machine Learning, AI Platform)

@ Phaidra | Remote

Sr. UI/UX Designer - Artificial Intelligence (ID:1213)

@ Truelogic Software | Remote, anywhere in LATAM

Analytics Engineer

@ carwow | London, England, United Kingdom

HRIS Data Analyst

@ SecurityScorecard | Remote