Papers Visual Tracking
“Visual Tracking” 태그가 달린 논문 581편 · 필터 해제
Deep Learning for Visual Tracking: A Comprehensive Survey
Visual target tracking is one of the most sought-after yet challenging research topics in computer vision. Given the ill-posed nature of the problem and its popularity in a broad range of real-world scenarios, a number o…
Deep LearningSurveyVisual TrackingSiam R-CNN: Visual Tracking by Re-Detection
We present Siam R-CNN, a Siamese re-detection architecture which unleashes the full power of two-stage object detection approaches for visual object tracking. We combine this with a novel tracklet-based dynamic programmi…
Objectobject-detectionObject DetectionObject Tracking+3TracKlinic: Diagnosis of Challenge Factors in Visual Tracking
Generic visual tracking is difficult due to many challenge factors (e.g., occlusion, blur, etc.). Each of these factors may cause serious problems for a tracking algorithm, and when they work together can make things eve…
Visual TrackingSiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking
By decomposing the visual tracking task into two subproblems as classification for pixel category and regression for object bounding box at this pixel, we propose a novel fully convolutional Siamese network to solve visu…
ClassificationGeneral ClassificationRegion Proposalregression+1SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines
Visual tracking problem demands to efficiently perform robust classification and accurate target state estimation over a given target at the same time. Former methods have proposed various ways of target state estimation…
ClassificationGeneral ClassificationRobust classificationState Estimation+2Deep Flow Collaborative Network for Online Visual Tracking
The deep learning-based visual tracking algorithms such as MDNet achieve high performance leveraging to the feature extraction ability of a deep neural network. However, the tracking efficiency of these trackers is not v…
Optical Flow EstimationSchedulingVisual TrackingROI Pooled Correlation Filters for Visual Tracking
The ROI (region-of-interest) based pooling method performs pooling operations on the cropped ROI regions for various samples and has shown great success in the object detection methods. It compresses the model size while…
object-detectionObject DetectionVisual TrackingMultivariate Uncertainty in Deep Learning
Deep learning has the potential to dramatically impact navigation and tracking state estimation problems critical to autonomous vehicles and robotics. Measurement uncertainties in state estimation systems based on Kalman…
Autonomous VehiclesDeep LearningPose EstimationState Estimation+3SPARK: Spatial-aware Online Incremental Attack Against Visual Tracking
Adversarial attacks of deep neural networks have been intensively studied on image, audio, natural language, patch, and pixel classification tasks. Nevertheless, as a typical, while important real-world application, the …
Adversarial AttackObject TrackingVideo Object TrackingVisual Object Tracking+1Hierarchical Feature-Aware Tracking
In this paper, we propose a hierarchical feature-aware tracking framework for efficient visual tracking. Recent years, ensembled trackers which combine multiple component trackers have achieved impressive performance. In…
Visual TrackingSuperpixel Tensor Pooling for Visual Tracking using Multiple Midlevel Visual Cues Fusion
In this paper, we propose a method called superpixel tensor pooling tracker which can fuse multiple midlevel cues captured by superpixels into sparse pooled tensor features. Our method first adopts the superpixel method …
SuperpixelsVisual TrackingDirect Visual-Inertial Odometry with Semi-Dense Mapping
The paper presents a direct visual-inertial odometry system. In particular, a tightly coupled nonlinear optimization based method is proposed by integrating the recent advances in direct dense tracking and Inertial Measu…
Sensor FusionVisual OdometryVisual TrackingEnergy-Based Models for Deep Probabilistic Regression
While deep learning-based classification is generally tackled using standardized approaches, a wide variety of techniques are employed for regression. In computer vision, one particularly popular such technique is that o…
Head Pose Estimationobject-detectionObject DetectionPose Estimation+3Inducing Stronger Object Representations in Deep Visual Trackers
Fully convolutional deep correlation networks are integral components of state-of- the-art approaches to single object visual tracking. It is commonly assumed that these networks perform tracking by detection by matching…
ObjectSaliency DetectionVisual TrackingVisual Tracking by means of Deep Reinforcement Learning and an Expert Demonstrator
In the last decade many different algorithms have been proposed to track a generic object in videos. Their execution on recent large-scale video datasets can produce a great amount of various tracking behaviours. New tre…
Deep Reinforcement Learningreinforcement-learningReinforcement LearningReinforcement Learning (RL)+1GradNet: Gradient-Guided Network for Visual Object Tracking
The fully-convolutional siamese network based on template matching has shown great potentials in visual tracking. During testing, the template is fixed with the initial target feature and the performance totally relies o…
ObjectObject TrackingTemplate MatchingVisual Object Tracking+1Human Following for Wheeled Robot with Monocular Pan-tilt Camera
Human following on mobile robots has witnessed significant advances due to its potentials for real-world applications. Currently most human following systems are equipped with depth sensors to obtain distance information…
Optical Flow EstimationVisual TrackingSaliency based Semi-supervised Learning for Orbiting Satellite Tracking
The trajectory and boundary of an orbiting satellite are fundamental information for on-orbit repairing and manipulation by space robots. This task, however, is challenging owing to the freely and rapidly motion of on-or…
SegmentationVisual TrackingDiscriminative and Robust Online Learning for Siamese Visual Tracking
The problem of visual object tracking has traditionally been handled by variant tracking paradigms, either learning a model of the object's appearance exclusively online or matching the object with the target in an offli…
Object TrackingVisual Object TrackingVisual TrackingLearning Reinforced Attentional Representation for End-to-End Visual Tracking
Although numerous recent tracking approaches have made tremendous advances in the last decade, achieving high-performance visual tracking remains a challenge. In this paper, we propose an end-to-end network model to lear…
Visual Tracking