Papers Visual Tracking
“Visual Tracking” 태그가 달린 논문 581편 · 필터 해제
Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition
This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior k…
General ClassificationMulti-Object TrackingObjectObject Recognition+3Good Features to Correlate for Visual Tracking
During the recent years, correlation filters have shown dominant and spectacular results for visual object tracking. The types of the features that are employed in these family of trackers significantly affect the perfor…
General ClassificationObjectObject TrackingVisual Object Tracking+1DCFNet: Discriminant Correlation Filters Network for Visual Tracking
Discriminant Correlation Filters (DCF) based methods now become a kind of dominant approach to online object tracking. The features used in these methods, however, are either based on hand-crafted features like HoGs, or …
image-classificationObject TrackingVisual TrackingEfficient Version-Space Reduction for Visual Tracking
Discrminative trackers, employ a classification approach to separate the target from its background. To cope with variations of the target shape and appearance, the classifier is updated online with different samples of …
Visual TrackingReal-time 3D Human Tracking for Mobile Robots with Multisensors
Acquiring the accurate 3-D position of a target person around a robot provides fundamental and valuable information that is applicable to a wide range of robotic tasks, including home service, navigation and entertainmen…
Sensor FusionVisual TrackingLearning Background-Aware Correlation Filters for Visual Tracking
Correlation Filters (CFs) have recently demonstrated excellent performance in terms of rapidly tracking objects under challenging photometric and geometric variations. The strength of the approach comes from its ability …
ObjectVideo Object TrackingVisual TrackingReal-time visual tracking by deep reinforced decision making
One of the major challenges of model-free visual tracking problem has been the difficulty originating from the unpredictable and drastic changes in the appearance of objects we target to track. Existing methods tackle th…
Deep Reinforcement LearningReal-Time Visual Trackingreinforcement-learningReinforcement Learning+2Tracking using Numerous Anchor points
In this paper, an online adaptive model-free tracker is proposed to track single objects in video sequences to deal with real-world tracking challenges like low-resolution, object deformation, occlusion and motion blur. …
ObjectObject LocalizationVisual TrackingDeep Reinforcement Learning for Visual Object Tracking in Videos
In this paper we introduce a fully end-to-end approach for visual tracking in videos that learns to predict the bounding box locations of a target object at every frame. An important insight is that the tracking problem …
Decision MakingDeep Reinforcement LearningObjectObject Tracking+6SafeDrive: A Robust Lane Tracking System for Autonomous and Assisted Driving Under Limited Visibility
We present an approach towards robust lane tracking for assisted and autonomous driving, particularly under poor visibility. Autonomous detection of lane markers improves road safety, and purely visual tracking is desira…
Autonomous DrivingLane DetectionVisual TrackingRobust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation
Visual tracking is a fundamental problem in computer vision. Recently, some deep-learning-based tracking algorithms have been achieving record-breaking performances. However, due to the high complexity of deep learning, …
Domain Adaptationimage-classificationImage ClassificationObject Tracking+1Deep Motion Features for Visual Tracking
Robust visual tracking is a challenging computer vision problem, with many real-world applications. Most existing approaches employ hand-crafted appearance features, such as HOG or Color Names. Recently, deep RGB feature…
Action RecognitionOptical Flow EstimationTemporal Action LocalizationVideo Classification+1Dual Deep Network for Visual Tracking
Visual tracking addresses the problem of identifying and localizing an unknown target in a video given the target specified by a bounding box in the first frame. In this paper, we propose a dual network to better utilize…
Visual TrackingVisual motion processing and human tracking behavior
The accurate visual tracking of a moving object is a human fundamental skill that allows to reduce the relative slip and instability of the object's image on the retina, thus granting a stable, high-quality vision. In or…
Visual TrackingSANet: Structure-Aware Network for Visual Tracking
Convolutional neural network (CNN) has drawn increasing interest in visual tracking owing to its powerfulness in feature extraction. Most existing CNN-based trackers treat tracking as a classification problem. However, t…
General ClassificationObjectVisual TrackingConvolutional Regression for Visual Tracking
Recently, discriminatively learned correlation filters (DCF) has drawn much attention in visual object tracking community. The success of DCF is potentially attributed to the fact that a large amount of samples are utili…
Object TrackingregressionVisual Object TrackingVisual TrackingVisual Tracking via Boolean Map Representations
In this paper, we present a simple yet effective Boolean map based representation that exploits connectivity cues for visual tracking. We describe a target object with histogram of oriented gradients and raw color featur…
Visual TrackingCounterfactual Reasoning about Intent for Interactive Navigation in Dynamic Environments
Many modern robotics applications require robots to function autonomously in dynamic environments including other decision making agents, such as people or other robots. This calls for fast and scalable interactive motio…
counterfactualCounterfactual ReasoningDecision MakingMotion Planning+2SPiKeS: Superpixel-Keypoints Structure for Robust Visual Tracking
In visual tracking, part-based trackers are attractive since they are robust against occlusion and deformation. However, a part represented by a rectangular patch does not account for the shape of the target, while a sup…
SuperpixelsVisual TrackingAdaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking
Tracking-by-detection methods have demonstrated competitive performance in recent years. In these approaches, the tracking model heavily relies on the quality of the training set. Due to the limited amount of labeled tra…
Visual Tracking