Results 11 to 20 of about 1,707,291 (329)
Masked-attention Mask Transformer for Universal Image Segmentation [PDF]
Computer Vision and Pattern Recognition, 2021 Image segmentation groups pixels with different semantics, e.g., category or instance membership. Each choice of semantics defines a task. While only the semantics of each task differ, current research focuses on designing spe-cialized architectures for ...
Bowen Cheng +4 more
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UNETR: Transformers for 3D Medical Image Segmentation [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2021 Fully Convolutional Neural Networks (FCNNs) with contracting and expanding paths have shown prominence for the majority of medical image segmentation applications since the past decade. In FCNNs, the encoder plays an integral role by learning both global
Ali Hatamizadeh +3 more
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UNet++: A Nested U-Net Architecture for Medical Image Segmentation [PDF]
DLMIA/ML-CDS@MICCAI, 2018 In this paper, we present UNet++, a new, more powerful architecture for medical image segmentation. Our architecture is essentially a deeply-supervised encoder-decoder network where the encoder and decoder sub-networks are connected through a series of ...
Zongwei Zhou +3 more
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Dual Attention Network for Scene Segmentation [PDF]
Computer Vision and Pattern Recognition, 2018 In this paper, we address the scene segmentation task by capturing rich contextual dependencies based on the self-attention mechanism. Unlike previous works that capture contexts by multi-scale features fusion, we propose a Dual Attention Networks (DANet)
J. Fu +4 more
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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
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Path Aggregation Network for Instance Segmentation [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in proposal-based instance segmentation framework.
Shu Liu +4 more
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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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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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V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation [PDF]
International Conference on 3D Vision, 2016 Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields. Despite their popularity, most approaches are only able to process 2D images while most medical data used ...
Fausto Milletarì +2 more
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Image Segmentation Using Deep Learning: A Survey [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, among others, and ...
Shervin Minaee +5 more
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