What Makes a Place? Building Bespoke Place Dependent Object Detectors for Robotics

7 Aug 2017 Jeffrey Hawke Alex Bewley Ingmar Posner

This paper is about enabling robots to improve their perceptual performance through repeated use in their operating environment, creating local expert detectors fitted to the places through which a robot moves. We leverage the concept of 'experiences' in visual perception for robotics, accounting for bias in the data a robot sees by fitting object detector models to a particular place... (read more)

PDF Abstract
No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet