CAP : Context-aware Pruning for semantic segmentation
Network pruning for deep convolutional neural networks (CNNs) has recently achieved notable research progress on image-level classification. However, most existing pruning methods are not catered to or evaluated on semantic segmentation networks. In this paper, we advocate the importance of contextu...
Main Authors: | He, Wei, Wu, Meiqing, Liang, Mingfu, Lam, Siew-Kei |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Conference Paper |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/147439 |
Similar Items
Exploiting visual context and consistency for semantic segmentation
by: Kang, Dang
Published: (2018)
by: Kang, Dang
Published: (2018)
Similar Items
-
SmooSeg: smoothness prior for unsupervised semantic segmentation
by: Lan, Mengcheng, et al.
Published: (2024) -
Exploiting visual context and consistency for semantic segmentation
by: Kang, Dang
Published: (2018) -
RGBD indoor semantic segmentation with segmentation transformer
by: Choong, Han Yi
Published: (2022) -
Semantic segmentation of delayered IC images with shape-variant convolution
by: Wang, Xue
Published: (2022) -
Context-aware pedestrian motion prediction
by: Haddad, Sirin
Published: (2021)