Papers Visual Tracking
“Visual Tracking” 태그가 달린 논문 581편 · 필터 해제
Transformer Tracking
Correlation acts as a critical role in the tracking field, especially in recent popular Siamese-based trackers. The correlation operation is a simple fusion manner to consider the similarity between the template and the …
GPUObject TrackingVideo Object TrackingVisual Object Tracking+1IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object Tracking
Adversarial attack arises due to the vulnerability of deep neural networks to perceive input samples injected with imperceptible perturbations. Recently, adversarial attack has been applied to visual object tracking to e…
Adversarial Attackimage-classificationImage ClassificationObject+3Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark
Unmanned Aerial Vehicles (UAV) can pose a major risk for aviation safety, due to both negligent and malicious use. For this reason, the automated detection and tracking of UAV is a fundamental task in aerial security sys…
object-detectionObject DetectionVisual TrackingTransformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking
In video object tracking, there exist rich temporal contexts among successive frames, which have been largely overlooked in existing trackers. In this work, we bridge the individual video frames and explore the temporal …
DecoderObjectObject TrackingVideo Object Tracking+2High precision control and deep learning-based corn stand counting algorithms for agricultural robot
This paper presents high precision control and deep learning-based corn stand counting algorithms for a low-cost, ultra-compact 3D printed and autonomous field robot for agricultural operations. Currently, plant traits, …
Model Predictive ControlVisual TrackingDCF-ASN: Coarse-to-fine Real-time Visual Tracking via Discriminative Correlation Filter and Attentional Siamese Network
Discriminative correlation filters (DCF) and siamese networks have achieved promising performance on visual tracking tasks thanks to their superior computational efficiency and reliable similarity metric learning, respec…
Computational EfficiencyMetric LearningReal-Time Visual TrackingVisual TrackingReal-Time Visual Object Tracking via Few-Shot Learning
Visual Object Tracking (VOT) can be seen as an extended task of Few-Shot Learning (FSL). While the concept of FSL is not new in tracking and has been previously applied by prior works, most of them are tailored to fit sp…
Few-Shot LearningObjectObject TrackingVisual Object Tracking+1Higher Performance Visual Tracking with Dual-Modal Localization
Visual Object Tracking (VOT) has synchronous needs for both robustness and accuracy. While most existing works fail to operate simultaneously on both, we investigate in this work the problem of conflicting performance be…
Object TrackingregressionVisual Object TrackingVisual TrackingPredictive Visual Tracking: A New Benchmark and Baseline Approach
As a crucial robotic perception capability, visual tracking has been intensively studied recently. In the real-world scenarios, the onboard processing time of the image streams inevitably leads to a discrepancy between t…
Visual TrackingRevisiting the details when evaluating a visual tracker
Visual tracking algorithms are naturally adopted in various applications, there have been several benchmarks and many tracking algorithms, more expected to appear in the future. In this report, I focus on single object t…
Object TrackingVisual TrackingCross-Attention Guided Network for Visual Tracking
Most traditional Siamese trackers are used to process the feature information of the template branch and search branch respectively, and to correlate with each other to get the location of the max response which regarded…
Visual TrackingHigh-Performance Discriminative Tracking With Transformers
End-to-end discriminative trackers improve the state of the art significantly, yet the improvement in robustness and efficiency is restricted by the conventional discriminative model, i.e., least-squares based regres…
DecoderObjectVisual TrackingVocal Bursts Intensity PredictionMLVSNet: Multi-Level Voting Siamese Network for 3D Visual Tracking
Benefiting from the excellent performance of Siamese-based trackers, huge progress on 2D visual tracking has been achieved. However, 3D visual tracking is still under-explored. Inspired by the idea of Hough voting in…
3D Object Detectionobject-detectionObject DetectionVisual TrackingSiamese Anchor Proposal Network for High-Speed Aerial Tracking
In the domain of visual tracking, most deep learning-based trackers highlight the accuracy but casting aside efficiency. Therefore, their real-world deployment on mobile platforms like the unmanned aerial vehicle (UAV) i…
Visual TrackingVocal Bursts Intensity PredictionMulti-modal Visual Tracking: Review and Experimental Comparison
Visual object tracking, as a fundamental task in computer vision, has drawn much attention in recent years. To extend trackers to a wider range of applications, researchers have introduced information from multiple modal…
Object TrackingRgb-T TrackingVisual Object TrackingVisual TrackingOnline Photometric Calibration of Automatic Gain Thermal Infrared Cameras
Thermal infrared cameras are increasingly being used in various applications such as robot vision, industrial inspection and medical imaging, thanks to their improved resolution and portability. However, the performance …
Camera Auto-CalibrationThermal Image DenoisingVisual OdometryVisual TrackingLearning to Fuse Asymmetric Feature Maps in Siamese Trackers
Recently, Siamese-based trackers have achieved promising performance in visual tracking. Most recent Siamese-based trackers typically employ a depth-wise cross-correlation (DW-XCorr) to obtain multi-channel correlation i…
Video Object TrackingVisual Object TrackingVisual TrackingOnline Decision Based Visual Tracking via Reinforcement Learning
A deep visual tracker is typically based on either object detection or template matching while each of them is only suitable for a particular group of scenes. It is straightforward to consider fusing them together to pur…
Hierarchical Reinforcement Learningobject-detectionObject Detectionreinforcement-learning+4Robust Correlation Tracking via Multi-channel Fused Features and Reliable Response Map
Benefiting from its ability to efficiently learn how an object is changing, correlation filters have recently demonstrated excellent performance for rapidly tracking objects. Designing effective features and handling mod…
ObjectVisual TrackingCRACT: Cascaded Regression-Align-Classification for Robust Visual Tracking
High quality object proposals are crucial in visual tracking algorithms that utilize region proposal network (RPN). Refinement of these proposals, typically by box regression and classification in parallel, has been popu…
ClassificationGeneral ClassificationRegion Proposalregression+1