Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation [PDF]
2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014 Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. The best-performing methods are complex ensemble systems that typically combine multiple low-level image features with high-level context.
Ross Girshick +3 more
openalex +3 more sources
Learning Deconvolution Network for Semantic Segmentation [PDF]
IEEE International Conference on Computer Vision, 2015 We propose a novel semantic segmentation algorithm by learning a deep deconvolution network. We learn the network on top of the convolutional layers adopted from VGG 16-layer net.
Hyeonwoo Noh +2 more
openalex +3 more sources
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016 In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit.
Liang-Chieh Chen +4 more
openalex +3 more sources
BiSeg: Simultaneous Instance Segmentation and Semantic Segmentation with Fully Convolutional Networks [PDF]
, 2017 We present a simple and effective framework for simultaneous semantic segmentation and instance segmentation with Fully Convolutional Networks (FCNs). The method, called BiSeg, predicts instance segmentation as a posterior in Bayesian inference, where ...
Ito, Satoshi +2 more
core +2 more sources
SEMANTIC SEGMENTATION OF INDOOR 3D POINT CLOUDS BY JOINT OPTIMIZATION OF GEOMETRIC FEATURES AND NEURAL NETWORKS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Indoor navigation, indoor robotics, and other deep applications of interior space can be realized through semantic segmentation of 3D point clouds. We propose a semantic segmentation method for point clouds that uses geometric features of point clouds ...
M. M. Yao +9 more
doaj +1 more source
Research Review of Image Semantic Segmentation Method in High-Resolution Remote Sensing Image Interpretation [PDF]
Jisuanji kexue yu tansuo, 2023 Rapid acquisition of remote sensing information has important research significance for the development of image semantic segmentation methods in remote sensing image interpretation applications.
MA Yan, Gulimila·Kezierbieke
doaj +1 more source
Segmenter: Transformer for Semantic Segmentation [PDF]
IEEE International Conference on Computer Vision, 2021 Image segmentation is often ambiguous at the level of individual image patches and requires contextual information to reach label consensus. In this paper we introduce Segmenter, a transformer model for semantic segmentation.
Robin Strudel +3 more
semanticscholar +1 more source
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers [PDF]
Computer Vision and Pattern Recognition, 2020 Most recent semantic segmentation methods adopt a fully-convolutional network (FCN) with an encoder-decoder architecture. The encoder progressively reduces the spatial resolution and learns more abstract/semantic visual concepts with larger receptive ...
Sixiao Zheng +10 more
semanticscholar +1 more source
Side Adapter Network for Open-Vocabulary Semantic Segmentation [PDF]
Computer Vision and Pattern Recognition, 2023 This paper presents a new framework for open-vocabulary semantic segmentation with the pre-trained vision-language model, named Side Adapter Network (SAN). Our approach models the semantic segmentation task as a region recognition problem. A side network
Mengde Xu +4 more
semanticscholar +1 more source
Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision [PDF]
Computer Vision and Pattern Recognition, 2021 In this paper, we study the semi-supervised semantic segmentation problem via exploring both labeled data and extra unlabeled data. We propose a novel consistency regularization approach, called cross pseudo supervision (CPS).
Xiaokang Chen +3 more
semanticscholar +1 more source