Papers Visual Object Tracking
“Visual Object Tracking” 태그가 달린 논문 369편 · 필터 해제
IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object Tracking
Adversarial attack arises due to the vulnerability of deep neural networks to perceive input samples injected with imperceptible perturbations. Recently, adversarial attack has been applied to visual object tracking to e…
Adversarial Attackimage-classificationImage ClassificationObject+3Weakly-Supervised Domain Adaptation of Deep Regression Trackers via Reinforced Knowledge Distillation
Deep regression trackers are among the fastest tracking algorithms available, and therefore suitable for real-time robotic applications. However, their accuracy is inadequate in many domains due to distribution shift and…
Domain AdaptationKnowledge DistillationregressionVisual Object TrackingBenchmarking Deep Trackers on Aerial Videos
In recent years, deep learning-based visual object trackers have achieved state-of-the-art performance on several visual object tracking benchmarks. However, most tracking benchmarks are focused on ground level videos, w…
AttributeBenchmarkingObjectObject Tracking+1Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking
In video object tracking, there exist rich temporal contexts among successive frames, which have been largely overlooked in existing trackers. In this work, we bridge the individual video frames and explore the temporal …
DecoderObjectObject TrackingVideo Object Tracking+2Real-Time Visual Object Tracking via Few-Shot Learning
Visual Object Tracking (VOT) can be seen as an extended task of Few-Shot Learning (FSL). While the concept of FSL is not new in tracking and has been previously applied by prior works, most of them are tailored to fit sp…
Few-Shot LearningObjectObject TrackingVisual Object Tracking+1Higher Performance Visual Tracking with Dual-Modal Localization
Visual Object Tracking (VOT) has synchronous needs for both robustness and accuracy. While most existing works fail to operate simultaneously on both, we investigate in this work the problem of conflicting performance be…
Object TrackingregressionVisual Object TrackingVisual TrackingPatchNet -- Short-range Template Matching for Efficient Video Processing
Object recognition is a fundamental problem in many video processing tasks, accurately locating seen objects at low computation cost paves the way for on-device video recognition. We propose PatchNet, an efficient convol…
Objectobject-detectionObject DetectionObject Recognition+5Phase Space Reconstruction Network for Lane Intrusion Action Recognition
In a complex road traffic scene, illegal lane intrusion of pedestrians or cyclists constitutes one of the main safety challenges in autonomous driving application. In this paper, we propose a novel object-level phase spa…
Action RecognitionAutonomous DrivingObjectObject Tracking+4All-Day Object Tracking for Unmanned Aerial Vehicle
Visual object tracking, which is representing a major interest in image processing field, has facilitated numerous real world applications. Among them, equipping unmanned aerial vehicle (UAV) with real time robust visual…
AllCPUObjectObject Tracking+1SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation
In this paper we introduce a Transformer-based approach to video object segmentation (VOS). To address compounding error and scalability issues of prior work, we propose a scalable, end-to-end method for VOS called Spars…
Inductive BiasMotion SegmentationObjectOne-shot visual object segmentation+6Semi-Automatic Annotation For Visual Object Tracking
We propose a semi-automatic bounding box annotation method for visual object tracking by utilizing temporal information with a tracking-by-detection approach. For detection, we use an off-the-shelf object detector which …
Incremental LearningObjectobject-detectionObject Detection+2Temporally-Transferable Perturbations: Efficient, One-Shot Adversarial Attacks for Online Visual Object Trackers
In recent years, the trackers based on Siamese networks have emerged as highly effective and efficient for visual object tracking (VOT). While these methods were shown to be vulnerable to adversarial attacks, as most dee…
Object TrackingVisual Object TrackingRotation Equivariant Siamese Networks for Tracking
Rotation is among the long prevailing, yet still unresolved, hard challenges encountered in visual object tracking. The existing deep learning-based tracking algorithms use regular CNNs that are inherently translation eq…
2D Pose EstimationBenchmarkingObject TrackingPose Estimation+1Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation
Visual object tracking aims to precisely estimate the bounding box for the given target, which is a challenging problem due to factors such as deformation and occlusion. Many recent trackers adopt the multiple-stage trac…
Object TrackingSemi-Supervised Video Object SegmentationVisual Object TrackingMulti-modal Visual Tracking: Review and Experimental Comparison
Visual object tracking, as a fundamental task in computer vision, has drawn much attention in recent years. To extend trackers to a wider range of applications, researchers have introduced information from multiple modal…
Object TrackingRgb-T TrackingVisual Object TrackingVisual TrackingLearning to Fuse Asymmetric Feature Maps in Siamese Trackers
Recently, Siamese-based trackers have achieved promising performance in visual tracking. Most recent Siamese-based trackers typically employ a depth-wise cross-correlation (DW-XCorr) to obtain multi-channel correlation i…
Video Object TrackingVisual Object TrackingVisual TrackingIs First Person Vision Challenging for Object Tracking?
Understanding human-object interactions is fundamental in First Person Vision (FPV). Tracking algorithms which follow the objects manipulated by the camera wearer can provide useful cues to effectively model such interac…
Human-Object Interaction DetectionObjectObject TrackingVisual Object Tracking+1Siamese Tracking with Lingual Object Constraints
Classically, visual object tracking involves following a target object throughout a given video, and it provides us the motion trajectory of the object. However, for many practical applications, this output is often insu…
ObjectObject TrackingQuestion AnsweringVideo Summarization+3AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection
Recent studies have shown that the performance of forgery detection can be improved with diverse and challenging Deepfakes datasets. However, due to the lack of Deepfakes datasets with large variance in appearance, which…
Visual Object TrackingLearning Spatio-Appearance Memory Network for High-Performance Visual Tracking
Existing visual object tracking usually learns a bounding-box based template to match the targets across frames, which cannot accurately learn a pixel-wise representation, thereby being limited in handling severe appeara…
Object TrackingSegmentationSemantic SegmentationVideo Object Segmentation+4