Papers Visual Object Tracking
“Visual Object Tracking” 태그가 달린 논문 369편 · 필터 해제
Rethinking Generic Object Tracking Toward Human-Level Perceptual Intelligence
At the heart of human visual perception lies the ability to maintain a continuous and coherent understanding of the external world. By integrating observations with accumulated experience, the human visual system can con…
Visual Object TrackingVisual TrackingSFDATrack: Generalized Source-Free Domain Adaptive Tracking Under Adverse Weather Conditions
Domain adaptive visual object tracking under adverse weather conditions has garnered significant attention in recent years. Despite the impressive performance, existing methods heavily rely on the large-scale video frame…
Visual Object TrackingSUMO: Segment and Track Any Motion with Nonlinear State Space Models
Visual Object Tracking (VOT) and Moving Object Segmentation (MOS) are two fundamental tasks in computer vision that involve both spatial and temporal object dynamics. Existing methods rely predominantly on visual cues an…
Visual Object TrackingObject SegmentationActive Adversarial Perturbation-driven Associative Memory Retrieval for RGB-Event Visual Object Tracking
RGB-Event tracking improves localization robustness by fusing RGB appearance textures and dense temporal motion cues from event sensors. While this multi-modal scheme broadens tracking applicability, real-world scenes su…
Visual Object TrackingSENTRY: SAM2-Enhanced Neighbor-Aware and Temporally Reasoned Memory for Visual Tracking
We revisit the memory update mechanism in SAM2-based visual object tracking and identify confidence-only mask selection as the dominant cause of drift under occlusion, rapid motion, and distractors. We introduce SENTRY, …
Visual Object TrackingVisual TrackingA Theory-grounded Hybrid Neural Network Integrating Complementary Estimation Mechanisms for Stable Visual Object TrackingA
Hybrid neural networks (HNNs) that integrate artificial neural networks (ANNs) with brain-inspired neural networks have achieved broad success across perception and control tasks. However, much of the current success is …
Visual Object TrackingVisual TrackingLeveraging Text-to-Image Diffusion Models for Unsupervised Visual Object Tracking
Unsupervised visual object tracking is a challenging task that requires following arbitrary targets in videos without training on ground-truth annotations. Despite considerable progress, existing state-of-the-art unsuper…
Visual Object TrackingImage GenerationSegment Anything with Motion, Geometry, and Semantic Adaptation for Complex Nonlinear Visual Object Tracking
Traditional visual object tracking (VOT) methods typically rely on task-specific supervised training, limiting their generalization to unseen objects and challenging scenarios with distractors, occlusion, and nonlinear m…
Visual Object TrackingRELO: Reinforcement Learning to Localize for Visual Object Tracking
Conventional visual object trackers localize targets using handcrafted spatial priors, often in the form of heatmaps. Such priors provide only surrogate supervision and are poorly aligned with tracking optimization and e…
Reinforcement LearningVisual Object TrackingAn Efficient Token Compression Framework for Visual Object Tracking
Refining visual representations by eliminating their internal feature-level redundancy is crucial for simultaneously optimizing the performance and computational cost of models in visual tracking. To enhance their perfor…
Visual Object TrackingVisual TrackingDynamic Pondering Sparsity-aware Mixture-of-Experts Transformer for Event Stream based Visual Object Tracking
Despite significant progress, RGB-based trackers remain vulnerable to challenging imaging conditions, such as low illumination and fast motion. Event cameras offer a promising alternative by asynchronously capturing pixe…
Computational EfficiencyVisual Object TrackingUnified Multimodal Visual Tracking with Dual Mixture-of-Experts
Multimodal visual object tracking can be divided into to several kinds of tasks (e.g. RGB and RGB+X tracking), based on the input modality. Existing methods often train separate models for each modality or rely on pretra…
Visual Object TrackingModel CompressionVisual TrackingSpatial Orthogonal Refinement for Robust RGB-Event Visual Object Tracking
Robust visual object tracking (VOT) remains challenging in high-speed motion scenarios, where conventional RGB sensors suffer from severe motion blur and performance degradation. Event cameras, with microsecond temporal …
Visual Object TrackingBeyond MACs: Hardware Efficient Architecture Design for Vision Backbones
Vision backbone networks play a central role in modern computer vision. Enhancing their efficiency directly benefits a wide range of downstream applications. To measure efficiency, many publications rely on MACs (Multipl…
Visual Object TrackingSemantic SegmentationImage ClassificationObject DetectionArchitecture and evaluation protocol for transformer-based visual object tracking in UAV applications
Object tracking from Unmanned Aerial Vehicles (UAVs) is challenged by platform dynamics, camera motion, and limited onboard resources. Existing visual trackers either lack robustness in complex scenarios or are too compu…
Visual Object TrackingUTPTrack: Towards Simple and Unified Token Pruning for Visual Tracking
One-stream Transformer-based trackers achieve advanced performance in visual object tracking but suffer from significant computational overhead that hinders real-time deployment. While token pruning offers a path to effi…
Visual Object TrackingVisual TrackingLayer-Guided UAV Tracking: Enhancing Efficiency and Occlusion Robustness
Visual object tracking (VOT) plays a pivotal role in unmanned aerial vehicle (UAV) applications. Addressing the trade-off between accuracy and efficiency, especially under challenging conditions like unpredictable occlus…
Representation LearningKnowledge DistillationVisual Object TrackingDecoupling Amplitude and Phase Attention in Frequency Domain for RGB-Event based Visual Object Tracking
Existing RGB-Event visual object tracking approaches primarily rely on conventional feature-level fusion, failing to fully exploit the unique advantages of event cameras. In particular, the high dynamic range and motion-…
Visual Object TrackingRethinking Memory Design in SAM-Based Visual Object Tracking
\noindent Memory has become the central mechanism enabling robust visual object tracking in modern segmentation-based frameworks. Recent methods built upon Segment Anything Model 2 (SAM2) have demonstrated strong perform…
Visual Object TrackingMSITrack: A Challenging Benchmark for Multispectral Single Object Tracking
Visual object tracking in real-world scenarios presents numerous challenges including occlusion, interference from similar objects and complex backgrounds-all of which limit the effectiveness of RGB-based trackers. Multi…
Visual Object Tracking