Search results with tag "Deeplab"
1 DeepLab: Semantic Image Segmentation with Deep ...
arxiv.org“DeepLab” system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reaching 79.7% mIOU in the test set, and advances the results on three other datasets: PASCAL-Context, PASCAL-Person-Part, and Cityscapes. All of our code is made publicly available online.
Structured Knowledge Distillation for Semantic Segmentation
openaccess.thecvf.comDeepLab [5, 6, 7, 48], PSPNet [56], OCNet [50], Re-fineNet [23] and DenseASPP [46] have achieved significant improvement in segmentation accuracy, often with cumber-some models and expensive computation. Recently, neural networks with small model size, light computation cost and high segmentation accuracy, have at-
平成 28 年度卒業論文 - miyazaki-u
cvlab.cs.miyazaki-u.ac.jp付き確率場を組み合わせたDeepLab[4]は、セマンティック・セグメンテーショ ンで粗い出力が生成される問題に対処しているが、十分ではなかった。 6
Encoder-DecoderwithAtrous Separable Convolution for ...
openaccess.thecvf.comresearch/deeplab. 2 Related Work Models based on Fully Convolutional Networks (FCNs) [8,11] have demonstrated significant improvement on several segmentation benchmarks [1,2,3,4,5]. There are several model variants proposed to exploit the contextual information for segmentation [12,13,14,15,16,17,32,33], including those that employ multi-scale
Semi-Supervised Semantic Segmentation With Directional ...
openaccess.thecvf.comSegmentation networks can not predict a label for each pixel merely based on its RGB values. Therefore, the con-textual information is essential for semantic segmentation. Iconic models (e.g., DeepLab [7] and PSPNet [60]) have also shown satisfying performance by adequately aggregat-ing the contextual cues to individual pixels before making