Auto-Fit: A Human-Machine Collaboration Feature for Fitting Bounding Box Annotations

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)(2020)

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摘要
Large high-quality annotated datasets are essential in training deep learning models, but are expensive and time-consuming to create. A large chunk of time in the annotation process goes into adjusting bounding boxes to fit the desired object. In this paper, we propose the facilitation of human machine collaboration through the creation of an Auto-Fit feature which automatically tightens an initia...
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关键词
Grabcut,background subtraction,CVAT,computer vision,annotations
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