Papers Visual Tracking
“Visual Tracking” 태그가 달린 논문 581편 · 필터 해제
Efficient Adversarial Attacks for Visual Object Tracking
Visual object tracking is an important task that requires the tracker to find the objects quickly and accurately. The existing state-ofthe-art object trackers, i.e., Siamese based trackers, use DNNs to attain high accura…
GPUObjectObject TrackingVisual Object Tracking+1PG-Net: Pixel to Global Matching Network for Visual Tracking
Siamese neural network has been well investigated by tracking frameworks due to its fast speed and high accuracy. However, very few efforts were spent on background-extraction by those approaches. In this paper, a Pixel …
Visual TrackingUnsupervised Deep Representation Learning for Real-Time Tracking
The advancement of visual tracking has continuously been brought by deep learning models. Typically, supervised learning is employed to train these models with expensive labeled data. In order to reduce the workload of m…
Representation LearningVisual TrackingScale Equivariance Improves Siamese Tracking
Siamese trackers turn tracking into similarity estimation between a template and the candidate regions in the frame. Mathematically, one of the key ingredients of success of the similarity function is translation equivar…
Object TrackingTranslationVisual Object TrackingVisual TrackingVisual Tracking by TridentAlign and Context Embedding
Recent advances in Siamese network-based visual tracking methods have enabled high performance on numerous tracking benchmarks. However, extensive scale variations of the target object and distractor objects with similar…
Region ProposalVisual TrackingTracking-by-Trackers with a Distilled and Reinforced Model
Visual object tracking was generally tackled by reasoning independently on fast processing algorithms, accurate online adaptation methods, and fusion of trackers. In this paper, we unify such goals by proposing a novel t…
Knowledge DistillationObject TrackingVideo Object TrackingVisual Object Tracking+1Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation
In recent years, the multiple-stage strategy has become a popular trend for visual tracking. This strategy first utilizes a base tracker to coarsely locate the target and then exploits a refinement module to obtain more …
Visual TrackingAccurate Bounding-box Regression with Distance-IoU Loss for Visual Tracking
Most existing trackers are based on using a classifier and multi-scale estimation to estimate the target state. Consequently, and as expected, trackers have become more stable while tracking accuracy has stagnated. While…
regressionVisual TrackingThe Heterogeneity Hypothesis: Finding Layer-Wise Differentiated Network Architectures
In this paper, we tackle the problem of convolutional neural network design. Instead of focusing on the design of the overall architecture, we investigate a design space that is usually overlooked, i.e. adjusting the cha…
image-classificationImage ClassificationImage RestorationVisual TrackingExemplar Loss for Siamese Network in Visual Tracking
Visual tracking plays an important role in perception system, which is a crucial part of intelligent transportation. Recently, Siamese network is a hot topic for visual tracking to estimate moving targets' trajectory, du…
TripletVisual TrackingCascaded Regression Tracking: Towards Online Hard Distractor Discrimination
Visual tracking can be easily disturbed by similar surrounding objects. Such objects as hard distractors, even though being the minority among negative samples, increase the risk of target drift and model corruption, whi…
regressionVisual TrackingDeep Convolutional Likelihood Particle Filter for Visual Tracking
We propose a novel particle filter for convolutional-correlation visual trackers. Our method uses correlation response maps to estimate likelihood distributions and employs these likelihoods as proposal densities to samp…
Visual TrackingVariational Inference and Learning of Piecewise-linear Dynamical Systems
Modeling the temporal behavior of data is of primordial importance in many scientific and engineering fields. Baseline methods assume that both the dynamic and observation equations follow linear-Gaussian models. However…
Head Pose EstimationModel SelectionPose EstimationPose Tracking+2Correlation-Guided Attention for Corner Detection Based Visual Tracking
Accurate bounding box estimation has recently attracted much attention in the tracking community because traditional multi-scale search strategies cannot estimate tight bounding boxes in many challenging scenarios involv…
Visual TrackingOne-Shot Adversarial Attacks on Visual Tracking With Dual Attention
Almost all adversarial attacks in computer vision are aimed at pre-known object categories, which could be offline trained for generating perturbations. But as for visual object tracking, the tracked target categories ar…
Adversarial AttackObjectObject TrackingVisual Object Tracking+1TLPG-Tracker: Joint Learning of Target Localization and Proposal Generation for Visual Tracking.
Target localization and proposal generation are two essential subtasks in generic visual tracking, and it is a challenge to address both the two efficiently. In this paper, we propose an efficient two-stage architecture …
Visual TrackingRobust Visual Object Tracking with Two-Stream Residual Convolutional Networks
The current deep learning based visual tracking approaches have been very successful by learning the target classification and/or estimation model from a large amount of supervised training data in offline mode. However,…
Object TrackingVisual Object TrackingVisual TrackingVocal Bursts Valence PredictionHow to Train Your Energy-Based Model for Regression
Energy-based models (EBMs) have become increasingly popular within computer vision in recent years. While they are commonly employed for generative image modeling, recent work has applied EBMs also for regression tasks, …
object-detectionObject DetectionregressionVisual Object Tracking+1Derivation of a Constant Velocity Motion Model for Visual Tracking
Motion models play a great role in visual tracking applications for predicting the possible locations of objects in the next frame. Unlike target tracking in radar or aerospace domain which considers only points, object …
Object TrackingVisual TrackingFully Convolutional Online Tracking
Online learning has turned out to be effective for improving tracking performance. However, it could be simply applied for classification branch, but still remains challenging to adapt to regression branch due to its com…
Real-Time Visual TrackingregressionVisual Tracking