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Dynamic Message Propagation Network for RGB-D Salient Object Detection
[article]
2022
arXiv
pre-print
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This paper presents a novel deep neural network framework for RGB-D salient object detection by controlling the message passing between the RGB images and depth maps on the feature level and exploring ...
the long-range semantic contexts and geometric information on both RGB and depth features to infer salient objects. ...
BiANet [41] proposes a multi-scale bilateral attention module (MBAM) to exploit global salient information in a multi-level manner. ...
arXiv:2206.09552v1
fatcat:rzcne743q5ewvedczwzkzkilo4
Attention-guided Context Feature Pyramid Network for Object Detection
[article]
2020
arXiv
pre-print
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For object detection, how to address the contradictory requirement between feature map resolution and receptive field on high-resolution inputs still remains an open question. ...
fields via integrating attention-guided multi-path features. ...
The Context Attention Module (CxAM) and Content Attention Module (CnAM) are devised to identify the salient dependencies among the extracted context. ...
arXiv:2005.11475v1
fatcat:em5vkhiltzespk2vx4co24mtbu
Scattering Keypoints Guided Network for Oriented Ship Detection in High-Resolution and Large-Scale SAR Images
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Moreover, these detectors have limited performance in large-scale and complex scenes due to the strong interference of inshore background and the variability of object imaging characteristics. ...
Second, a contextaware feature selection module is introduced to dynamically learn both local and context features. ...
One direct way of acquiring the context information is multi-scale feature fusion. ...
doi:10.1109/jstars.2021.3109469
fatcat:4lxmv5pw5bagzbpp6cfkvles5q
HROM: Learning High-Resolution Representation and Object-Aware Masks for Visual Object Tracking
2020
Sensors
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Moreover, we exploit attention mechanisms to learn object-aware masks for adaptive feature refinement, and use deformable convolution to handle complex geometric transformations. ...
The resulting representation is semantically richer and spatially more precise by a simple yet effective multi-scale feature fusion strategy. ...
are exploited to perform up-sample process for object detection. ...
doi:10.3390/s20174807
pmid:32858872
fatcat:m2gcbfyklzfylbpehtqnm3m5bu
Deformable ConvNets v2: More Deformable, Better Results
[article]
2018
arXiv
pre-print
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With the proposed contributions, this new version of Deformable ConvNets yields significant performance gains over the original model and produces leading results on the COCO benchmark for object detection ...
The superior performance of Deformable Convolutional Networks arises from its ability to adapt to the geometric variations of objects. ...
In a multi-path network for object detection [40] , multiple RoIpooling layers are employed for each input RoI to better exploit multi-scale and context information. ...
arXiv:1811.11168v2
fatcat:goo53jnvorgahpar4qdglm6bdy
iMSCGnet: Iterative Multi-scale Context-guided Segmentation of Skin Lesion in Dermoscopic Images
2020
IEEE Access
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INDEX TERMS Skin lesion segmentation, multi-scale context, attention, deep supervision. ...
To alleviate this problem, we propose a multi-scale context-guided network named as MSCGnet to segment the skin lesions accurately. ...
A and + are the context-based attention structure CAs and the element-wise addition, respectively. ...
doi:10.1109/access.2020.2974512
fatcat:nwfoe4dthjbojpnbuwdh6wtmzi
Salience-Guided Cascaded Suppression Network for Person Re-Identification
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Acknowledgement This work is supported in part by the National Natural Science Foundation of China under Grant 61972188, the Science and Technology Planning Project of Shenzhen (No. ...
Channel-wise Attention: The high-level convolutional feature in a trained CNN module is well-known to have remarkable localization ability for a semantic-related object. ...
Residual Dual Attention Module The Residual Dual Attention Module (RDAM) consists of a Channel-wise Attention Module(CAM) and a Residual Spatial Attention Module (RSAM), in which the channel-wise attention ...
doi:10.1109/cvpr42600.2020.00336
dblp:conf/cvpr/ChenFZZSJY20
fatcat:ujz4jyuirjabnicda3eemo547y
MPViT: Multi-Path Vision Transformer for Dense Prediction
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2112.11010v1 fatcat:lnrdvmflfrajfld662ykkjsy7e
Dense computer vision tasks such as object detection and segmentation require effective multi-scale feature representation for detecting or classifying objects or regions with varying sizes. ...
classification, object detection, instance segmentation, and semantic segmentation. ...
These results demonstrate the proposed multi-scale patch embedding and multipath structure can represent more diverse multi-scale features than simpler multi-scale structured models for object detection ...
arXiv:2112.11010v2
fatcat:mk6uiqrinbborohzy7s2jj7cri
Research on Salient Object Detection using Deep Learning and Segmentation Methods
2019
International journal of recent technology and engineering
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Detecting and segmenting salient objects in natural scenes, often referred to as salient object detection has attracted a lot of interest in computer vision and recently various heuristic computational ...
The aim of this review work is to study about the details of methods in salient object detection. ...
Low-frequency content in the
image.
8
Automatic Salient Object
Detection in UAV Imagery
Sokalski,
[2010]
Multi-scale mean-shift segmentation
with novel histogram enhancement. ...
doi:10.35940/ijrte.b1046.0982s1119
fatcat:6ofq53vb7zhx7boq4ndpraphs4
2020 Index IEEE Transactions on Image Processing Vol. 29
2020
IEEE Transactions on Image Processing
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., +, TIP 2020 8590-8605 Reverse Attention-Based Residual Network for Salient Object Detection. Chen, S., +, TIP 2020 3763-3776 RGB-T Salient Object Detection via Fusing Multi-Level CNN Features. ...
., +, TIP 2020 670-678
Dynamic Feature Integration for Simultaneous Detection of Salient Object,
Edge, and Skeleton. ...
doi:10.1109/tip.2020.3046056
fatcat:24m6k2elprf2nfmucbjzhvzk3m
Visual Object Tracking with Saliency Refiner and Adaptive Updating
2018
International Journal of Innovative Computing, Information and Control
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Meanwhile, a separate scale filter is exploited to estimate the scale variation. ...
In this paper, we propose a novel correlation tracking approach with saliency refiner and adaptive updating. ...
This work is supported by the National Natural Science Foundation of China (Grant Nos: 61772421, 61572400) and the Key Research Project of Baoji University of Arts and Sciences (No: ZK15032). ...
doi:10.24507/ijicic.14.05.1855
fatcat:wkgqs4xcnvgc5l4uthec2bqg6m
Instance-Level Relative Saliency Ranking with Graph Reasoning
[article]
2021
arXiv
pre-print
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Conventional salient object detection models cannot differentiate the importance of different salient objects. ...
However, one of these models cannot differentiate object instances and the other focuses more on sequential attention shift order inference. ...
Some models [19] , [24] , [25] treat salient object detection as a pixel/superpixel-wise classification problem and run deep classification models on multi-scale regions. ...
arXiv:2107.03824v1
fatcat:2hhm6p3jv5h2fhtiefrpm55aee
Heterogeneous Grid Convolution for Adaptive, Efficient, and Controllable Computation
[article]
2021
arXiv
pre-print
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We have evaluated the proposed approach on four image understanding tasks, semantic segmentation, object localization, road extraction, and salient object detection. ...
Especially, the method outperforms a strong baseline with more than 90% reduction in floating-point operations for semantic segmentation, and achieves the state-of-the-art result for road extraction. ...
Acknowledgement This paper is partially based on results obtained from a project commissioned by the New Energy and Industrial Technology Development Organization (NEDO) and supported by JSPS KAKENHI Grant ...
arXiv:2104.11176v1
fatcat:4lkbvzvkgzadfe7dgqm6ah4sgq
An Adaptive Sample Assignment Strategy Based on Feature Enhancement for Ship Detection in SAR Images
2022
Remote Sensing
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Recently, ship detection in synthetic aperture radar (SAR) images has received extensive attention. ...
In order to alleviate false alarms, a feature aggregation enhancement pyramid network (FAEPN) is proposed to enhance multi-scale feature representations and suppress the interference of background noise ...
[26] designed a novel two-way structure to extract multi-scale context features efficiently. ...
doi:10.3390/rs14092238
fatcat:eb42cvyg2venpc3zd4eo3yneuy
2021 Index IEEE Transactions on Image Processing Vol. 30
2021
IEEE Transactions on Image Processing
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Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. ...
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
., +, TIP 2021 4526-4539 Looking for the Detail and Context Devils: High-Resolution Salient Object Detection. ...
doi:10.1109/tip.2022.3142569
fatcat:z26yhwuecbgrnb2czhwjlf73qu
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