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Centralized Feature Pyramid for Object Detection
IEEE Transactions on Image Processing, 2023 Visual feature pyramid has shown its superiority in both effectiveness and efficiency in a wide range of applications. However, the existing methods exorbitantly concentrate on the inter-layer feature interactions but ignore the intra-layer feature regulations, which are empirically proved beneficial.
Yu Quan +3 more
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Panoptic Feature Pyramid Networks [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 The recently introduced panoptic segmentation task has renewed our community's interest in unifying the tasks of instance segmentation (for thing classes) and semantic segmentation (for stuff classes). However, current state-of-the-art methods for this joint task use separate and dissimilar networks for instance and semantic segmentation, without ...
Kirillov, Alexander +3 more
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Class Feature Pyramids for Video Explanation [PDF]
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2019 Deep convolutional networks are widely used in video action recognition. 3D convolutions are one prominent approach to deal with the additional time dimension. While 3D convolutions typically lead to higher accuracies, the inner workings of the trained models are more difficult to interpret. We focus on creating human-understandable visual explanations
Stergiou, A.G. +5 more
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Fast Feature Pyramids for Object Detection [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014 Multi-resolution image features may be approximated via extrapolation from nearby scales, rather than being computed explicitly. This fundamental insight allows us to design object detection algorithms that are as accurate, and considerably faster, than the state-of-the-art.
Dollár, Piotr +3 more
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Global Feature Pyramid Network
, 2023 dataset not ...
Xiao, Weilin, Xu, Ming, Lin, Yonggui
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Key morphological features of human pyramidal neurons
Cerebral Cortex, 2023 AbstractThe basic building block of the cerebral cortex, the pyramidal cell, has been shown to be characterized by a markedly different dendritic structure among layers, cortical areas, and species. Functionally, differences in the structure of their dendrites and axons are critical in determining how neurons integrate information.
Benavides Piccione, Ruth +5 more
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Pyramid Feature Attention Network for Saliency Detection [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Saliency detection is one of the basic challenges in computer vision. How to extract effective features is a critical point for saliency detection. Recent methods mainly adopt integrating multi-scale convolutional features indiscriminately. However, not all features are useful for saliency detection and some even cause interferences.
Zhao, Ting, Wu, Xiangqian
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Volumetric Semantic Segmentation Using Pyramid Context Features [PDF]
2013 IEEE International Conference on Computer Vision, 2013 We present an algorithm for the per-voxel semantic segmentation of a three-dimensional volume. At the core of our algorithm is a novel "pyramid context" feature, a descriptive representation designed such that exact per-voxel linear classification can be made extremely efficient.
Jonathan T, Barron +5 more
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Pyramid-Net: Intra-layer Pyramid-Scale Feature Aggregation Network for Retinal Vessel Segmentation [PDF]
Frontiers in Medicine, 2021 Retinal vessel segmentation plays an important role in the diagnosis of eye-related diseases and biomarkers discovery. Existing works perform multi-scale feature aggregation in an inter-layer manner, namely inter-layer feature aggregation. However, such an approach only fuses features at either a lower scale or a higher scale, which may result in a ...
Jiawei Zhang +16 more
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