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Furthermore, we design a Guided Aggregation Layer to enhance mutual connections and fuse both types of feature representation. Besides, a booster training strategy is designed to improve the …
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We propose an attention-guided aggregation stereo matching network, which can encode and integrate feature information multiple times in the entire network. The …
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FedQL: Q-Learning Guided Aggregation for Federated Learning. Authors: Mei Cao, Mengying Zhao, Tingting Zhang, Nanxiang Yu, Jianbo Lu Authors Info & Claims. Algorithms and Architectures for Parallel Processing: 23rd International Conference, ICA3PP 2023, Tianjin, China, October 20–22, 2023, Proceedings, Part I.
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To address these limitations, we propose a multi-scale attention-guided progressive aggregation network (MAPANet) to progressively restore the target contrast MR images from the corresponding low resolution (LR) observations with the assistance of auxiliary contrast images. Specifically, the proposed MAPANet is composed of several stacked …
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This work proposes an accurate and efficient network called Attention‐guided Aggregation and Error‐aware Enhancement Network (AAEE‐Net), which achieves state‐of‐the‐art performance with low inference time and qualitative results show that AAEE‐ net significantly improves predictions, especially for thin structures. Stereo matching is a …
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In the experiments, we show that nets with a two-layer guided aggregation block easily outperform the state-of-the-art GC-Net which has nineteen 3D convolutional …
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Stereo image dense matching, which plays a key role in 3D reconstruction, remains a challenging task in photogrammetry and computer vision. In addition to block-based matching, recent studies based on artificial neural networks have achieved great progress in stereo matching by using deep convolutional networks. This study proposes …
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Dual-modal imaging-guided agent based on NIR-II aggregation-induced emission luminogens with balanced phototheranostic performance Chem Sci. 2024 Jun 7;15 (28):10969 ... These nanoparticles were applied to fluorescence-photothermal dual-mode imaging-guided photothermal ablation in a HeLa tumor xenograft mouse model, …
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In the experiments, we show that nets with a two-layer guided aggregation block easily outperform the state-of-the-art GC-Net which has nineteen 3D convolutional layers. We also train a deep guided aggregation network (GA-Net) which gets better accuracies than state-of-the-art methods on both Scene Flow dataset and KITTI benchmarks.
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To the best of our knowledge, the proposed work is both the first self-guided and first local cost aggregation method based on the deep learning approach. In summary, this paper makes the following contributions. -We introduce a self-guided cost aggregation method for stereo matching that does not require any guidance color image.-
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We design a guided aggregation layer to enhance mutual connections and fuse both types of feature representation. Moreover, a booster training strategy is designed to improve the segmentation performance without any extra inference cost. Extensive quantitative and qualitative evaluations demonstrate that the proposed architecture …
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The relation-guided aggregation module aims to capture rich attributes of entities, which generates the sub-structures according to relation types, and aggregates semantic information among them. To dig out the contribution of different relation types to the central entity, relation-guided interaction module is proposed to calculate the ...
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@inproceedings{Zhang2019GANet, title={GA-Net: Guided Aggregation Net for End-to-end Stereo Matching}, author={Zhang, Feihu and Prisacariu, Victor and Yang, Ruigang and Torr, Philip HS}, booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition}, pages={185--194}, year={2019} } About. GA-Net: Guided Aggregation …
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In the stereo matching task, matching cost aggregation is crucial in both traditional methods and deep neural network models in order to accurately estimate disparities. We …
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Here, we present a DNA framework-guided strategy to prepare highly luminescent metal cluster nanoaggregates. Our approach involves an amphiphilic DNA framework comprising a hydrophobic alkyl core and a rigid DNA framework shell, serving as a nucleation site and providing well-defined nanoconfinements for the self-limiting …
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We design a guided aggregation layer to enhance mutual connections and fuse both types of feature representation. Moreover, a booster training strategy is designed to improve the segmentation performance without any extra inference cost.
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This work addresses cross-view camera pose estimation, i.e., determining the 3-Degrees-of-Freedom camera pose of a given ground-level image w.r.t. an aerial image of the local area. We propose SliceMatch, which consists of ground and aerial feature extractors, feature aggregators, and a pose predictor. The feature extractors …
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Download Citation | Guided aggregation and disparity refinement for real-time stereo matching | Stereo matching methods based on convolution neural network (CNN) often face challenges such as edge ...
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Nowadays, CNN-based stereo matching methods achieved remarkable performance, and how to efficiently exploit contextual information in cost aggregation stage is the key to improve performance. In this paper, we propose a simple yet efficient network named Hierarchical Context Guided Aggregation Network (HCGANet). Specifically, a novel …
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In this paper, the guided patch cost aggregation module and the combination of guided disparity map upsampling and coarse-to-fine method for disparity …
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GA-Net is a novel deep learning model for estimating disparities from stereo images. It uses two guided aggregation layers to capture local and global cost …
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•We propose a novel item-guided aggregation framework for FedRec and the existing FedRec models can be regarded as the instantiation of our framework. •We propose a novel item semantic alignment mechanism for the federated cold-start recommendation, and the overall algorithm can be formulated into a unified federated opti-mization framework.
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Applying synthetic aperture radar automatic target recognition (SAR ATR) in open scenario based on deep learning (DL) is challenging due to the difficulty in incrementally recognizing new targets with limited samples. To address this challenge, we introduce simulated data that reflects the structure and scattering features of the new …
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BiSeNet V2 is a bilateral network that separates spatial details and categorical semantics for high accuracy and efficiency. It uses a guided aggregation …
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Flow-Guided Feature Aggregation (FGFA) is initially described in an ICCV 2017 paper.It provides an accurate and end-to-end learning framework for video object detection. The proposed FGFA method, together with our previous work of Deep Feature Flow, powered the winning entry of ImageNet VID 2017.It is worth noting that:
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ing priors-guided aggregation network, named CPGA. The CPGA consists of three modules: the inter-frame temporal aggregation (ITA) module, the multi-scale non-local aggre-gation (MNA) module and the quality enhancement (QE) module. Specifically, the ITA module explores the inter-frame correlations among the multiple compressed frames
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We also train a deep guided aggregation network (GA-Net) which gets better accuracies than state-of-the-art methods on both Scene Flow dataset and KITTI benchmarks. In the stereo matching task, matching cost aggregation is crucial in both traditional methods and deep neural network models in order to accurately estimate disparities. We propose ...
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A tree-guided anisotropic aggregation strategy is proposed for message passing. Within this strategy, the message is passed along paths in a hierarchical tree-like hypergraph with substructures of the original graph as its nodes. In parallel, the intensity of message passing is constrained adaptively by an effective gating mechanism.
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We proposed a deep-supervision-guided feature aggregation network based on a U-shape structure with ResNet as the backbone network for mangrove detection and segmentation. The construction of the dataset was achieved through the utilization of QGIS software version 3.28 (QGIS is released under the GPL Version 2 or any later version). ...
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