Papers Visual Tracking
“Visual Tracking” 태그가 달린 논문 581편 · 필터 해제
CHASE: Robust Visual Tracking via Cell-Level Differentiable Neural Architecture Search
A strong visual object tracker nowadays relies on its well-crafted modules, which typically consist of manually-designed network architectures to deliver high-quality tracking results. Not surprisingly, the manual design…
Neural Architecture SearchSemantic SegmentationVisual TrackingDifferentiable Particle Filters through Conditional Normalizing Flow
Differentiable particle filters provide a flexible mechanism to adaptively train dynamic and measurement models by learning from observed data. However, most existing differentiable particle filters are within the bootst…
Visual TrackingSelf-Supervised Tracking via Target-Aware Data Synthesis
While deep-learning based tracking methods have achieved substantial progress, they entail large-scale and high-quality annotated data for sufficient training. To eliminate expensive and exhaustive annotation, we study s…
Representation LearningSelf-Supervised LearningVisual TrackingProgressive Unsupervised Learning for Visual Object Tracking
In this paper, we propose a progressive unsupervised learning (PUL) framework, which entirely removes the need for annotated training videos in visual tracking. Specifically, we first learn a background discriminatio…
Contrastive LearningObjectObject TrackingVisual Object Tracking+1Towards Distraction-Robust Active Visual Tracking
In active visual tracking, it is notoriously difficult when distracting objects appear, as distractors often mislead the tracker by occluding the target or bringing a confusing appearance. To address this issue, we propo…
Visual TrackingDomain Adaptive SiamRPN++ for Object Tracking in the Wild
Benefit from large-scale training data, recent advances in Siamese-based object tracking have achieved compelling results on the normal sequences. Whilst Siamese-based trackers assume training and test data follow an ide…
Domain AdaptationObjectobject-detectionObject Detection+3Mutation Sensitive Correlation Filter for Real-Time UAV Tracking with Adaptive Hybrid Label
Unmanned aerial vehicle (UAV) based visual tracking has been confronted with numerous challenges, e.g., object motion and occlusion. These challenges generally introduce unexpected mutations of target appearance and resu…
Visual TrackingTracking Without Re-recognition in Humans and Machines
Imagine trying to track one particular fruitfly in a swarm of hundreds. Higher biological visual systems have evolved to track moving objects by relying on both appearance and motion features. We investigate if state-of-…
Decision MakingObjectObject TrackingVisual TrackingSuperevents: Towards Native Semantic Segmentation for Event-based Cameras
Most successful computer vision models transform low-level features, such as Gabor filter responses, into richer representations of intermediate or mid-level complexity for downstream visual tasks. These mid-level repres…
Depth EstimationSemantic SegmentationVisual TrackingTrTr: Visual Tracking with Transformer
Template-based discriminative trackers are currently the dominant tracking methods due to their robustness and accuracy, and the Siamese-network-based methods that depend on cross-correlation operation between features e…
DecoderVisual TrackingA Simple and Strong Baseline for Universal Targeted Attacks on Siamese Visual Tracking
Siamese trackers are shown to be vulnerable to adversarial attacks recently. However, the existing attack methods craft the perturbations for each video independently, which comes at a non-negligible computational cost. …
Visual TrackingSpatio-Temporal Matching for Siamese Visual Tracking
Similarity matching is a core operation in Siamese trackers. Most Siamese trackers carry out similarity learning via cross correlation that originates from the image matching field. However, unlike 2-D image matching, th…
Object TrackingVisual TrackingEquivalence of Correlation Filter and Convolution Filter in Visual Tracking
(Discriminative) Correlation Filter has been successfully applied to visual tracking and has advanced the field significantly in recent years. Correlation filter-based trackers consider visual tracking as a problem of ma…
Edge DetectionVisual TrackingOcclusion-aware Visual Tracker using Spatial Structural Information and Dominant Features
To overcome the problem of occlusion in visual tracking, this paper proposes an occlusion-aware tracking algorithm. The proposed algorithm divides the object into discrete image patches according to the pixel distributio…
ClusteringVisual TrackingSiamCorners: Siamese Corner Networks for Visual Tracking
The current Siamese network based on region proposal network (RPN) has attracted great attention in visual tracking due to its excellent accuracy and high efficiency. However, the design of the RPN involves the selection…
Region ProposalVisual TrackingTarget Transformed Regression for Accurate Tracking
Accurate tracking is still a challenging task due to appearance variations, pose and view changes, and geometric deformations of target in videos. Recent anchor-free trackers provide an efficient regression mechanism but…
regressionVisual Object TrackingVisual TrackingSTMTrack: Template-free Visual Tracking with Space-time Memory Networks
Boosting performance of the offline trained siamese trackers is getting harder nowadays since the fixed information of the template cropped from the first frame has been almost thoroughly mined, but they are poorly capab…
Video Object TrackingVisual Object TrackingVisual TrackingLearning Spatio-Temporal Transformer for Visual Tracking
In this paper, we present a new tracking architecture with an encoder-decoder transformer as the key component. The encoder models the global spatio-temporal feature dependencies between target objects and search regions…
DecoderObject TrackingVideo Object TrackingVisual Object Tracking+1Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark
Tracking by natural language specification is a new rising research topic that aims at locating the target object in the video sequence based on its language description. Compared with traditional bounding box (BBox) bas…
2kObjectObject TrackingSentence+2Learning Target Candidate Association to Keep Track of What Not to Track
The presence of objects that are confusingly similar to the tracked target, poses a fundamental challenge in appearance-based visual tracking. Such distractor objects are easily misclassified as the target itself, leadin…
Object TrackingVideo Object TrackingVisual Object TrackingVisual Tracking