Results 21 to 30 of about 1,762,979 (356)
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation [PDF]
Computer Vision and Pattern Recognition, 2016 Point cloud is an important type of geometric data structure. Due to its irregular format, most researchers transform such data to regular 3D voxel grids or collections of images. This, however, renders data unnecessarily voluminous and causes issues. In
C. Qi, Hao Su, Kaichun Mo, L. Guibas
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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
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Equipartition of a Segment [PDF]
Mathematics of Operations Research, 2023 We prove that, for any positive integer m, a segment may be partitioned into m possibly degenerate or empty segments with equal values of a continuous function f evaluated on segments, assuming that f may take positive and negative values, but its value on degenerate or empty segments is zero. Funding: S.
Sergey Avvakumov, Roman Karasev
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Development, 2019 ABSTRACT There is now compelling evidence that many arthropods pattern their segments using a clock-and-wavefront mechanism, analogous to that operating during vertebrate somitogenesis. In this Review, we discuss how the arthropod segmentation clock generates a repeating sequence of pair-rule gene expression, and how this is converted ...
Clark, Erik +2 more
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Fully convolutional networks for semantic segmentation [PDF]
Computer Vision and Pattern Recognition, 2014 Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, exceed the state-of-the-art in semantic segmentation.
Evan Shelhamer +2 more
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Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models [PDF]
Computer Vision and Pattern Recognition, 2023 We present ODISE: Open-vocabulary DIffusion-based panoptic SEgmentation, which unifies pre-trained text-image diffusion and discriminative models to perform open-vocabulary panoptic segmentation. Text-to-image diffusion models have the remarkable ability
Jiarui Xu +5 more
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Online Segment to Segment Neural Transduction [PDF]
Proceedings of the 2016 Conference on Empirical Methods in Natural
Language Processing, 2016 We introduce an online neural sequence to sequence model that learns to alternate between encoding and decoding segments of the input as it is read. By independently tracking the encoding and decoding representations our algorithm permits exact polynomial marginalization of the latent segmentation during training, and during decoding beam search is ...
Yu, L, Buys, J, Blunsom, P
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Joint Learning of Intrinsic Images and Semantic Segmentation [PDF]
, 2018 Semantic segmentation of outdoor scenes is problematic when there are variations in imaging conditions. It is known that albedo (reflectance) is invariant to all kinds of illumination effects. Thus, using reflectance images for semantic segmentation task
A Garcia-Garcia +13 more
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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
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Customized Segment Anything Model for Medical Image Segmentation [PDF]
arXiv.org, 2023 We propose SAMed, a general solution for medical image segmentation. Different from the previous methods, SAMed is built upon the large-scale image segmentation model, Segment Anything Model (SAM), to explore the new research paradigm of customizing ...
Kaiwen Zhang, Dong Liu
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