Bottom-up top-down cues for weakly-supervised semantic segmentation
We consider the task of learning a classifier for semantic segmentation using weak supervision in the form of image labels specifying objects present in the image. Our method uses deep convolutional neural networks (cnns) and adopts an Expectation-Maximization (EM) based approach. We focus on the fo...
Главные авторы: | Hou, Q, Massiceti, D, Dokania, P, Wei, Y, Cheng, M, Torr, P |
---|---|
Формат: | Conference item |
Опубликовано: |
Springer, Cham
2018
|
Схожие документы
-
OBJCUT: efficient segmentation using top-down and bottom-up cues.
по: Kumar, M, и др.
Опубликовано: (2010) -
OBJCUT: efficient segmentation using top-down and bottom-up cues
по: Kumar, MP, и др.
Опубликовано: (2009) -
Discovering class-specific pixels for weakly-supervised semantic segmentation
по: Chaudhry, A, и др.
Опубликовано: (2017) -
Exploring bottom-up and top-down cues with attentive learning for webly supervised object detection
по: Wu, Zhonghua, и др.
Опубликовано: (2020) -
Bottom-up or top-down?
по: Johansen-Berg, H
Опубликовано: (2001)