Results 11 to 20 of about 986,520 (234)
Texture-Aware Superpixel Segmentation [PDF]
2019 IEEE International Conference on Image Processing (ICIP), 2019 Most superpixel algorithms compute a trade-off between spatial and color features at the pixel level. Hence, they may need fine parameter tuning to balance the two measures, and highly fail to group pixels with similar local texture properties. In this paper, we address these issues with a new Texture-Aware SuperPixel (TASP) method.
Giraud, Rémi +3 more
core +5 more sources
Superpixel Segmentation With Fully Convolutional Networks [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 In computer vision, superpixels have been widely used as an effective way to reduce the number of image primitives for subsequent processing. But only a few attempts have been made to incorporate them into deep neural networks.
Feng-Ting Yang +3 more
semanticscholar +6 more sources
Robust Semantic Segmentation with Superpixel-Mix
Proceedings of the British Machine Vision Conference 2021, 2021 Accepted to ...
Gianni Franchi +6 more
core +6 more sources
Rethinking Unsupervised Neural Superpixel Segmentation [PDF]
2022 IEEE International Conference on Image Processing (ICIP), 2022 Recently, the concept of unsupervised learning for superpixel segmentation via CNNs has been studied. Essentially, such methods generate superpixels by convolutional neural network (CNN) employed on a single image, and such CNNs are trained without any ...
Moshe Eliasof +2 more
semanticscholar +3 more sources
Medial Features for Superpixel Segmentation. [PDF]
, 2009 Image segmentation plays an important role in computer vision and human scene perception. Image oversegmentation is a common technique to overcome the problem of managing the high number of pixels and the reasoning among them. Specifically, a local and coherent cluster that contains a statistically homogeneous region is denoted as a superpixel. In this
Engel, D. +5 more
openaire +3 more sources
International Journal of Digital EarthIn the field of remote sensing, using a large amount of labeled image data to supervise the training of fully convolutional networks for the semantic segmentation of images is expensive.
Zenan Yang +4 more
doaj +2 more sources
USNet: underwater image superpixel segmentation via multi-scale water-net
Frontiers in Marine ScienceUnderwater images commonly suffer from a variety of quality degradations, such as color casts, low contrast, blurring details, and limited visibility.
Chuhong Wang +6 more
doaj +2 more sources
A Two-Stage Gradient Ascent-Based Superpixel Framework for Adaptive Segmentation
Applied Sciences, 2019 Superpixel segmentation usually over-segments an image into fragments to extract regional features, thus linking up advanced computer vision tasks. In this work, a novel coarse-to-fine gradient ascent framework is proposed for superpixel-based color ...
Wangpeng He +4 more
doaj +2 more sources
COMPARATIVE ANALYSIS OF SUPERPIXEL SEGMENTATION METHODS
International Journal of Engineering Technologies and Management Research, 2020 Superpixel segmentation showed to be a useful preprocessing step in many computer vision applications. Superpixel’s purpose is to reduce the redundancy in the image and increase efficiency from the point of view of the next processing task. This led to a variety of algorithms to compute superpixel segmentations, each with individual strengths and ...
SumitKaur, Dr. R.K Bansal
openaire +4 more sources
Multiobjective Evolutionary Superpixel Segmentation for PolSAR Image Classification
Remote SensingSuperpixel segmentation has been widely used in the field of computer vision. The generations of PolSAR superpixels have also been widely studied for their feasibility and high efficiency.
Boce Chu +7 more
doaj +2 more sources