A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
Siamese Attentional Keypoint Network for High Performance Visual Tracking
[article]
2019
arXiv
pre-print
Preserved Fulltext
Other Versions
Firstly, a new Siamese lightweight hourglass network is specifically designed for visual tracking. ...
Network, dubbed SATIN, to achieve efficient tracking and accurate localization. ...
detection module for object detection and localization. ...
arXiv:1904.10128v1
fatcat:ovn4s5cbdfbkllioy7fxnqxp5q
Visual Tracking by TridentAlign and Context Embedding
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
To address these persisting issues, we propose novel TridentAlign and context embedding modules for Siamese network-based visual tracking methods. ...
Recent advances in Siamese network-based visual tracking methods have enabled high performance on numerous tracking benchmarks. ...
Along with the wide application of convolutional neural networks (CNNs) to various computer vision tasks [1, 2, 3] , recent advances in Siamese networkbased visual tracking methods [4, 5, 6, 7] have ...
arXiv:2007.06887v1
fatcat:laskvl6xl5egliwmy53w22b544
Deep Object Tracking with Shrinkage Loss
2020
IEEE Transactions on Pattern Analysis and Machine Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
In this paper, we address the issue of data imbalance in learning deep models for visual object tracking. ...
When replacing the original binary cross-entropy loss with our shrinkage loss, three representative baseline trackers achieve large performance gains, even setting new state-of-the-art results. ...
Most conferences do not use the Author Gateway; authors of conference articles should feel free to post their own version of their articles as accepted for publication by an IEEE conference, with the addition ...
doi:10.1109/tpami.2020.3041332
pmid:33253114
fatcat:cf3u3gbnjzcj3i7quidfv7zkbi
Siamese Visual Object Tracking: A Survey
2021
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
[59] proposed their Hierarchical spatial-aware Siamese convolutional neural network (HSSNet) for TIR object tracking. ...
As far as the target-detection network was concerned, they adopted a single-stage YOLOv3-like [95] approach with dilated convolutions to expand the receptive fields for more granular object detection ...
Trackers marked with symbol "*" deal with a specific task of TIR tracking and not standard VOT.
Tracker Year ...
doi:10.1109/access.2021.3101988
fatcat:iwjlqirwqrav5nadbaw2g5huuu
Rail track condition monitoring: a review on deep learning approaches
2021
Intelligence & Robotics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Potential challenges and opportunities are discussed for the research community to decide on possible directions. ...
Rail track is a critical component of rail systems. Accidents or interruptions caused by rail track anomalies usually possess severe outcomes. ...
A context module and a plug-and-play structure are introduced for multi-scale reasoning using a stack of dilated convolutions on a feature map. • PSPNet utilizes a pyramid parsing module to exploit global ...
doi:10.20517/ir.2021.14
fatcat:7a7p6nqvtre4thatkaqb76asn4
Siamese Object Tracking for Unmanned Aerial Vehicle: A Review and Comprehensive Analysis
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
As an emerging force in the revolutionary trend of deep learning, Siamese networks shine in UAV-based object tracking with their promising balance of accuracy, robustness, and speed. ...
In the end, prospects for the development of Siamese tracking for UAV-based intelligent transportation systems are deeply discussed. ...
with the Siamese network to perform object tracking. ...
arXiv:2205.04281v2
fatcat:kaujdfb7ivdtxeiz44lu36oqum
Research on Rejoining Bone Stick Fragment Images: A Method Based on Multi-Scale Feature Fusion Siamese Network Guided by Edge Contour
2024
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2024; you can also visit the original URL.
The file type is application/pdf.
Constructing a Siamese network framework, it first uses a residual network to extract features of bone sticks, which is followed by computing the L2 distance for similarity measurement. ...
This paper introduces a multi-scale feature fusion Siamese network guided by edge contour (MFS-GC) model. ...
Acknowledgments: This research was supported by experts from the Shaanxi Institute for the Preservation of Cultural Heritage, and we express our thanks for their assistance. ...
doi:10.3390/app14020717
fatcat:crd6wgeohbhqrhhmw2cadwxxem
SiamCAM: A Real-Time Siamese Network for Object Tracking with Compensating Attention Mechanism
2022
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
We propose a real-time Siamese network object tracking algorithm combined with a compensating attention mechanism to solve this problem. ...
The Siamese-based object tracking algorithm regards tracking as a similarity matching problem. ...
Conflicts of Interest: The authors declared no potential conflict of interest with respect to the research, authorship, and/or publication of this article. ...
doi:10.3390/app12083931
fatcat:6cl4lyek55gdfprygsoll7ymuy
Towards Visible and Thermal Drone Monitoring with Convolutional Neural Networks
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
To track a small flying drone, we utilize the residual information between consecutive image frames. ...
Finally, we present an integrated detection and tracking system that outperforms the performance of each individual module containing detection or tracking only. ...
SPPnet [5] develops spatial pyramid pooling on shared convolutional feature maps for efficient object detection and semantic segmentation. ...
arXiv:1812.08333v1
fatcat:otgm7vy7w5gcpo7gpmnp47cuoy
Pseudo‐Siamese residual atrous pyramid network for multi‐focus image fusion
2021
IET Image Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Inspired by this, new Pseudo-Siamese neural network with several residual atrous convolution pyramids with multi-level perception ability to perceive the multi-level features and consistency relations ...
This situation restricts the further image processing, such as semantic segmentation, object recognition and 3D reconstruction. ...
After that, we combine the atrous convolution with the feature pyramid with the residual structure to form the residual atrous convolution pyramid (RACP) to extract features from multiple receptive fields ...
doi:10.1049/ipr2.12326
fatcat:jyhezmovf5cd7ljis6m4zhefji
Towards Visible and Thermal Drone Monitoring with Convolutional Neural Networks
2019
APSIPA Transactions on Signal and Information Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
To track a small flying drone, we utilize the residual information between consecutive image frames. ...
Finally, we present an integrated detection and tracking system that outperforms the performance of each individual module containing detection or tracking only. ...
SPPnet [5] develops spatial pyramid pooling on shared convolutional feature maps for efficient object detection and semantic segmentation. ...
doi:10.1017/atsip.2018.30
fatcat:ki7iz4sdanfq5pvxxe7typqzny
Multi-Task Driven Feature Models for Thermal Infrared Tracking
2020
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Second, we design a fine-grained aware module to capture more subtle information for distinguishing the TIR objects belonging to the same class. ...
Specifically, we first use an auxiliary classification network to guide the generation of TIR-specific discriminative features for distinguishing the TIR objects belonging to different classes. ...
modules, which provide more powerful features for target localization. ...
doi:10.1609/aaai.v34i07.6828
fatcat:upry6btsijdkjbdawd2aceyeq4
Multi-Task Driven Feature Models for Thermal Infrared Tracking
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Second, we design a fine-grained aware module to capture more subtle information for distinguishing the TIR objects belonging to the same class. ...
Specifically, we first use an auxiliary classification network to guide the generation of TIR-specific discriminative features for distinguishing the TIR objects belonging to different classes. ...
EDCF (Wang et al. 2018b ) jointly trains a low-level fine-grained matching and high-level semantic matching tasks on a Siamese framework for object tracking. ...
arXiv:1911.11384v1
fatcat:i72up27qovgtrlglvikf3n7gzq
Aerial Video Trackers Review
2020
Entropy
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The tracking algorithms are classified according to the type of target, and the target tracking algorithms that are based on deep learning are classified according to the network structure. ...
In this paper, the research status of aerial video tracking and the characteristics, background complexity and tracking diversity of aerial video targets are summarized. ...
[55] Similar objectives Common scenario Single target Siamese network SiamFC [76] Target deformation General background Single target PTAV [80] Common objectives Common scenario Single target SiamRPN ...
doi:10.3390/e22121358
pmid:33266268
pmcid:PMC7761283
fatcat:xlrcyulsjzeq7bjxe3fgmnuhrq
MRC-Net: 6-DoF Pose Estimation with MultiScale Residual Correlation
[article]
2024
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2024; you can also visit the original URL.
The file type is application/pdf.
Other Versions
MRC-Net employs a Siamese network with shared weights between both stages to learn embeddings for input and rendered images. ...
We propose a single-shot approach to determining 6-DoF pose of an object with available 3D computer-aided design (CAD) model from a single RGB image. Our method, dubbed MRC-Net, comprises two stages. ...
To capture local and global features, we use Atrous Spatial Pyramid Pooling (ASPP) [5] modules before both classifier and regressor. ...
arXiv:2403.08019v3
fatcat:7dwfe2np2bbttgbo4d2mxxk4lm
« Previous
Showing results 1 — 15 out of 262 results