全卷积多类多实例学习

Dec, 2014

Fully Convolutional Multi-Class Multiple Instance Learning

Deepak Pathak, Evan Shelhamer, Jonathan Long, Trevor Darrell

TL;DR本文提出了一种利用多实例学习（MIL）方法进行多类语义分割的学习的新算法，只需要通过图像级标记进行训练，同时采用全卷积网络来优化细分标签的分配。实验结果表明，该方法在PASCAL VOC数据集的分割挑战任务中有良好的表现。

Abstract

multiple instance learning (MIL) can reduce the need for costly annotation in tasks such as semantic segmentation by weakening the required degree of supervision. We propose a novel MIL formulation of multi-class