May 24, 2016 · We propose in this paper a training protocol based on the self-paced learning paradigm. The main idea is to iteratively select a subset of images and boxes ...
In this paper we adopt a self-paced learning approach to handle the uncertainty related to the BB-level localization of the objects in the training images in a ...
In this paper we propose a self-paced learning protocol to alleviate this problem. The main idea is to iteratively select a subset of samples that are most ...
We propose in this paper a training protocol based on the self-paced learning paradigm. The main idea is to iteratively select a subset of images and boxes ...
[PDF] Self Paced Deep Learning for Weakly Supervised Object Detection
www.semanticscholar.org › paper
This paper is the first showing that a self-paced approach can be used with deep-network-based classifiers in an end-to-end training pipeline, built on the ...
Self Paced Deep Learning for Weakly Supervised Object Detection
dl.acm.org › doi › TPAMI.2018.2804907
In a weakly-supervised scenario object detectors need to be trained using image-level annotation alone. Since bounding-box-level ground truth is not ...
Self-paced deep learning is a framework for weakly supervised object detection with deep ConvNets.
May 24, 2016 · Weakly supervised learning of object detection is an important problem in image understanding that still does not have a satisfactory solution.
In this paper, we propose to make a weak detector “train” itself through exploiting a novel deep self-taught learning approach such that it progressively gains ...
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Duration: 7:09
Posted: Sep 20, 2023
Posted: Sep 20, 2023