Web: http://arxiv.org/abs/2209.06535

Sept. 15, 2022, 1:13 a.m. | Youngseok Kim, Sanmin Kim, Jun Won Choi, Dongsuk Kum

cs.CV updates on arXiv.org arxiv.org

Camera and radar sensors have significant advantages in cost, reliability,
and maintenance compared to LiDAR. Existing fusion methods often fuse the
outputs of single modalities at the result-level, called the late fusion
strategy. This can benefit from using off-the-shelf single sensor detection
algorithms, but late fusion cannot fully exploit the complementary properties
of sensors, thus having limited performance despite the huge potential of
camera-radar fusion. Here we propose a novel proposal-level early fusion
approach that effectively exploits both spatial and …

arxiv detection fusion radar transformer

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

Postdoctoral Fellow: ML for autonomous materials discovery

@ Lawrence Berkeley National Lab | Berkeley, CA

Research Scientists

@ ODU Research Foundation | Norfolk, Virginia

Embedded Systems Engineer (Robotics)

@ Neo Cybernetica | Bedford, New Hampshire

2023 Luis J. Alvarez and Admiral Grace M. Hopper Postdoc Fellowship in Computing Sciences

@ Lawrence Berkeley National Lab | San Francisco, CA

Senior Manager Data Scientist

@ NAV | Remote, US

Senior AI Research Scientist

@ Earth Species Project | Remote anywhere

Research Fellow- Center for Security and Emerging Technology (Multiple Opportunities)

@ University of California Davis | Washington, DC

Staff Fellow - Data Scientist

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Staff Fellow - Senior Data Engineer

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Research Engineer - VFX, Neural Compositing

@ Flawless | Los Angeles, California, United States

[Job-TB] Senior Data Engineer

@ CI&T | Brazil

Data Analytics Engineer

@ The Fork | Paris, France