Papers Visual Tracking
“Visual Tracking” 태그가 달린 논문 581편 · 필터 해제
Kernalised Multi-resolution Convnet for Visual Tracking
Visual tracking is intrinsically a temporal problem. Discriminative Correlation Filters (DCF) have demonstrated excellent performance for high-speed generic visual object tracking. Built upon their seminal work, there ha…
Object TrackingVisual Object TrackingVisual TrackingCREST: Convolutional Residual Learning for Visual Tracking
Discriminative correlation filters (DCFs) have been shown to perform superiorly in visual tracking. They only need a small set of training samples from the initial frame to generate an appearance model. However, existing…
Visual TrackingParallel Tracking and Verifying: A Framework for Real-Time and High Accuracy Visual Tracking
Being intensively studied, visual tracking has seen great recent advances in either speed (e.g., with correlation filters) or accuracy (e.g., with deep features). Real-time and high accuracy tracking algorithms, however,…
Visual TrackingAttentional Correlation Filter Network for Adaptive Visual Tracking
We propose a new tracking framework with an attentional mechanism that chooses a subset of the associated correlation filters for increased robustness and computational efficiency. The subset of filters is adaptively sel…
Computational EfficiencyVisual Object TrackingVisual TrackingRobust Visual Tracking via Hierarchical Convolutional Features
In this paper, we propose to exploit the rich hierarchical features of deep convolutional neural networks to improve the accuracy and robustness of visual tracking. Deep neural networks trained on object recognition data…
Object RecognitionVisual TrackingAn In-Depth Analysis of Visual Tracking with Siamese Neural Networks
This survey presents a deep analysis of the learning and inference capabilities in nine popular trackers. It is neither intended to study the whole literature nor is it an attempt to review all kinds of neural networks p…
Visual TrackingAction-Decision Networks for Visual Tracking With Deep Reinforcement Learning
This paper proposes a novel tracker which is controlled by sequentially pursuing actions learned by deep reinforcement learning. In contrast to the existing trackers using deep networks, the proposed tracker is designed …
Deep Reinforcement LearningGPUreinforcement-learningReinforcement Learning+2BranchOut: Regularization for Online Ensemble Tracking With Convolutional Neural Networks
We propose an extremely simple but effective regularization technique of convolutional neural networks (CNNs), referred to as BranchOut, for online ensemble tracking. Our algorithm employs a CNN for target representatio…
DiversityVisual TrackingMulti-Task Correlation Particle Filter for Robust Object Tracking
In this paper, we propose a multi-task correlation particle filter (MCPF) for robust visual tracking. We first present the multi-task correlation filter (MCF) that takes the interdependencies among different features int…
ObjectObject TrackingVisual TrackingRobust Visual Tracking Using Oblique Random Forests
Random forest has emerged as a powerful classification technique with promising results in various vision tasks including image classification, pose estimation and object detection. However, current techniques have shown…
General Classificationimage-classificationImage ClassificationIncremental Learning+4Independent Motion Detection with Event-driven Cameras
Unlike standard cameras that send intensity images at a constant frame rate, event-driven cameras asynchronously report pixel-level brightness changes, offering low latency and high temporal resolution (both in the order…
Motion DetectionVisual TrackingLearning Spatial-Aware Regressions for Visual Tracking
In this paper, we analyze the spatial information of deep features, and propose two complementary regressions for robust visual tracking. First, we propose a kernelized ridge regression model wherein the kernel value is …
regressionVisual Object TrackingVisual TrackingFaster Spatially Regularized Correlation Filters for Visual Tracking
Discriminatively learned correlation filters (DCF) have been widely used in online visual tracking filed due to its simplicity and efficiency. These methods utilize a periodic assumption of the training samples to constr…
Visual TrackingDevelopment of a N-type GM-PHD Filter for Multiple Target, Multiple Type Visual Tracking
We propose a new framework that extends the standard Probability Hypothesis Density (PHD) filter for multiple targets having $N\geq2$ different types based on Random Finite Set theory, taking into account not only backgr…
Visual TrackingVocal Bursts Type PredictionLong-term Correlation Tracking using Multi-layer Hybrid Features in Sparse and Dense Environments
Tracking a target of interest in both sparse and crowded environments is a challenging problem, not yet successfully addressed in the literature. In this paper, we propose a new long-term visual tracking algorithm, learn…
Visual TrackingRobust Tracking Using Region Proposal Networks
Recent advances in visual tracking showed that deep Convolutional Neural Networks (CNN) trained for image classification can be strong feature extractors for discriminative trackers. However, due to the drastic differenc…
ClassificationFeature EngineeringGeneral Classificationimage-classification+3Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects
Robust object tracking requires knowledge and understanding of the object being tracked: its appearance, its motion, and how it changes over time. A tracker must be able to modify its underlying model and adapt to new ob…
ObjectObject TrackingregressionVisual TrackingTraX: The visual Tracking eXchange Protocol and Library
In this paper we address the problem of developing on-line visual tracking algorithms. We present a specialized communication protocol that serves as a bridge between a tracker implementation and utilizing application. I…
Visual TrackingAdaptive Feature Representation for Visual Tracking
Robust feature representation plays significant role in visual tracking. However, it remains a challenging issue, since many factors may affect the experimental performance. The existing method which combine different fe…
Visual TrackingReal-Time Salient Closed Boundary Tracking via Line Segments Perceptual Grouping
This paper presents a novel real-time method for tracking salient closed boundaries from video image sequences. This method operates on a set of straight line segments that are produced by line detection. The tracking sc…
Line DetectionVisual Tracking