July 25, 2022, 1:12 a.m. | Jinrong Yang, Lin Song, Songtao Liu, Zeming Li, Xiaoping Li, Hongbin Sun, Jian Sun, Nanning Zheng

cs.CV updates on arXiv.org arxiv.org

Many point-based 3D detectors adopt point-feature sampling strategies to drop
some points for efficient inference. These strategies are typically based on
fixed and handcrafted rules, making difficult to handle complicated scenes.
Different from them, we propose a Dynamic Ball Query (DBQ) network to
adaptively select a subset of input points according to the input features, and
assign the feature transform with suitable receptive field for each selected
point. It can be embedded into some state-of-the-art 3D detectors and trained
in …

3d arxiv cv detection query ssd

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Data Management Assistant

@ World Vision | Amman Office, Jordan

Cloud Data Engineer, Global Services Delivery, Google Cloud

@ Google | Buenos Aires, Argentina