Multi-scale volumes for deep object detection and localization

作者：

Highlights：

• Multi-scale feature reasoning for deep object detection in images is analyzed.

• A multi-scale contextual reasoning approach is proposed using multi-scale volumes.

• Scale-specific, joint detection and localization models increase robustness.

• The approach efficiently handles challenging cases of large variation in scale.

摘要

Highlights•Multi-scale feature reasoning for deep object detection in images is analyzed.•A multi-scale contextual reasoning approach is proposed using multi-scale volumes.•Scale-specific, joint detection and localization models increase robustness.•The approach efficiently handles challenging cases of large variation in scale.

论文关键词：Multi-scale reasoning,Context modeling,Efficient detection with deep features,Scale variation handling,Structured prediction

论文评审过程：Received 1 February 2016, Revised 8 May 2016, Accepted 2 June 2016, Available online 11 June 2016, Version of Record 13 October 2016.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.06.002