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Synthesizing Training Images for Semantic Segmentation
2018Semantic segmentation is one of the key problems in the computer vision area. Recently, Convolutional Neural Networks (CNNs) have yielded a significant performance for the semantic segmentation task. However, CNNs require a sufficient amount of annotated training images, which is challenging since massive human labour is needed.
Yunhui Zhang +3 more
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Statistical image modeling for semantic segmentation
IEEE Transactions on Consumer Electronics, 2010Semantic image segmentation (SIS) is one of the most crucial steps toward image understanding. In this paper, a novel framework to enable SIS is proposed by modeling images automatically. The statistical model for an image is automatically obtained by using a finite mixture model to approximate the underlying class distributions of image pixels.
Zhongjie Zhu, Yuer Wang, Gangyi Jiang
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Semantic segmentation of high-resolution images
Science China Information Sciences, 2017Image semantic segmentation is a research topic that has emerged recently. Although existing approaches have achieved satisfactory accuracy, they are limited to handling low-resolution images owing to their large memory consumption. In this paper, we present a semantic segmentation method for high-resolution images. First, we downsample the input image
Juhong Wang, Bin Liu, Kun Xu 0003
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On the use of regions for semantic image segmentation
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing, 2012There is a general trend in recent methods to use image regions (i.e. super-pixels) obtained in an unsupervised way to enhance the semantic image segmentation task. This paper proposes a detailed study on the role and the benefit of using these regions, at different steps of the segmentation process.
Rui Hu 0007 +2 more
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Semantic Image Segmentation and Object Labeling
IEEE Transactions on Circuits and Systems for Video Technology, 2007In this paper, we present a framework for simultaneous image segmentation and object labeling leading to automatic image annotation. Focusing on semantic analysis of images, it contributes to knowledge-assisted multimedia analysis and bridging the gap between semantics and low level visual features.
Thanos Athanasiadis +3 more
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Semantic Texton Forests for Image Categorization and Segmentation
2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008We propose semantic texton forests, efficient and powerful new low-level features. These are ensembles of decision trees that act directly on image pixels, and therefore do not need the expensive computation of filter-bank responses or local descriptors.
Jamie Shotton +2 more
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Semantic Segmentation of Equirectangular Images with UniFuse
2022 IEEE 11th Global Conference on Consumer Electronics (GCCE), 2022Atsushi Yokota, Shigang Li
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Improved methods and analysis for semantic image segmentation
2020Modernes “deep learning" hat in den letzten Jahren erstaunliche Entwicklungen im Bereich Computer Vision ermöglicht (Hinton and Salakhutdinov, 2006; Krizhevsky et al., 2012). Eine grundlegende Aufgabe der semantischen Segmentierung ist es, labels für jedes Pixel von Bildern vorherzusagen, wodurch die Wahrnehmung der visuellen Welt durch Maschinen ...
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FISS GAN: A Generative Adversarial Network for Foggy Image Semantic Segmentation
IEEE/CAA Journal of Automatica Sinica, 2021Fei-Yue Wang, Long Chen, Hongyan Guo
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Synergy between Semantic Segmentation and Image Denoising via Alternate Boosting
ACM Transactions on Multimedia Computing, Communications and Applications, 2023Dong Liu, Zhiwei Xiong
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