Papers Visual Object Tracking
“Visual Object Tracking” 태그가 달린 논문 369편 · 필터 해제
Correlation-Embedded Transformer Tracking: A Single-Branch Framework
Developing robust and discriminative appearance models has been a long-standing research challenge in visual object tracking. In the prevalent Siamese-based paradigm, the features extracted by the Siamese-like networks a…
Feature CorrelationObject TrackingVisual Object TrackingUnifying Visual and Vision-Language Tracking via Contrastive Learning
Single object tracking aims to locate the target object in a video sequence according to the state specified by different modal references, including the initial bounding box (BBOX), natural language (NL), or both (NL+BB…
Contrastive LearningObject TrackingVisual GroundingVisual Object Tracking+1Dense Optical Flow Estimation Using Sparse Regularizers from Reduced Measurements
Optical flow is the pattern of apparent motion of objects in a scene. The computation of optical flow is a critical component in numerous computer vision tasks such as object detection, visual object tracking, and activi…
Activity RecognitionMotion Estimationobject-detectionObject Detection+3Explicit Visual Prompts for Visual Object Tracking
How to effectively exploit spatio-temporal information is crucial to capture target appearance changes in visual tracking. However, most deep learning-based trackers mainly focus on designing a complicated appearance mod…
ObjectObject TrackingVisual Object TrackingVisual TrackingODTrack: Online Dense Temporal Token Learning for Visual Tracking
Online contextual reasoning and association across consecutive video frames are critical to perceive instances in visual tracking. However, most current top-performing trackers persistently lean on sparse temporal relati…
Semi-Supervised Video Object SegmentationVideo Object TrackingVisual Object TrackingVisual TrackingDiffusionTrack: Point Set Diffusion Model for Visual Object Tracking
Existing Siamese or transformer trackers commonly pose visual object tracking as a one-shot detection problem i.e. locating the target object in a single forward evaluation scheme. Despite the demonstrated success th…
DenoisingObject TrackingVisual Object TrackingVisual TrackingARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe
We present ARTrackV2, which integrates two pivotal aspects of tracking: determining where to look (localization) and how to describe (appearance analysis) the target object across video frames. Building on the foundation…
ObjectObject TrackingTemplate MatchingVideo Object Tracking+1X Modality Assisting RGBT Object Tracking
Learning robust multi-modal feature representations is critical for boosting tracking performance. To this end, we propose a novel X Modality Assisting Network (X-Net) to shed light on the impact of the fusion paradigm b…
Knowledge DistillationObjectObject TrackingOptical Flow Estimation+2Tracking Skiers from the Top to the Bottom
Skiing is a popular winter sport discipline with a long history of competitive events. In this domain, computer vision has the potential to enhance the understanding of athletes' performance, but its application lags beh…
Object TrackingVisual Object TrackingHIPTrack: Visual Tracking with Historical Prompts
Trackers that follow Siamese paradigm utilize similarity matching between template and search region features for tracking. Many methods have been explored to enhance tracking performance by incorporating tracking histor…
Visual Object TrackingVisual TrackingAViTMP: A Tracking-Specific Transformer for Single-Branch Visual Tracking
Visual object tracking is a fundamental component of transportation systems, especially for intelligent driving. Despite achieving state-of-the-art performance in visual tracking, recent single-branch trackers tend to ov…
DecoderObject TrackingVisual Object TrackingVisual TrackingDistractor-aware Event-based Tracking
Event cameras, or dynamic vision sensors, have recently achieved success from fundamental vision tasks to high-level vision researches. Due to its ability to asynchronously capture light intensity changes, event camera h…
ObjectObject TrackingVisual Object TrackingPutting the Object Back into Video Object Segmentation
We present Cutie, a video object segmentation (VOS) network with object-level memory reading, which puts the object representation from memory back into the video object segmentation result. Recent works on VOS employ bo…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+3Event Stream-based Visual Object Tracking: A High-Resolution Benchmark Dataset and A Novel Baseline
Tracking using bio-inspired event cameras has drawn more and more attention in recent years. Existing works either utilize aligned RGB and event data for accurate tracking or directly learn an event-based tracker. The fi…
Knowledge DistillationObject TrackingTransfer LearningVisual Object Tracking+1RTrack: Accelerating Convergence for Visual Object Tracking via Pseudo-Boxes Exploration
Single object tracking (SOT) heavily relies on the representation of the target object as a bounding box. However, due to the potential deformation and rotation experienced by the tracked targets, the genuine bounding bo…
Objectobject-detectionObject DetectionObject Tracking+1BASE: Probably a Better Approach to Multi-Object Tracking
The field of visual object tracking is dominated by methods that combine simple tracking algorithms and ad hoc schemes. Probabilistic tracking algorithms, which are leading in other fields, are surprisingly absent from t…
Multi-Object TrackingObjectObject TrackingVisual Object Tracking+1Leveraging the Power of Data Augmentation for Transformer-based Tracking
Due to long-distance correlation and powerful pretrained models, transformer-based methods have initiated a breakthrough in visual object tracking performance. Previous works focus on designing effective architectures su…
Data AugmentationObject TrackingVisual Object TrackingMobile Vision Transformer-based Visual Object Tracking
The introduction of robust backbones, such as Vision Transformers, has improved the performance of object tracking algorithms in recent years. However, these state-of-the-art trackers are computationally expensive since …
GPUObjectObject TrackingVisual Object TrackingSeparable Self and Mixed Attention Transformers for Efficient Object Tracking
The deployment of transformers for visual object tracking has shown state-of-the-art results on several benchmarks. However, the transformer-based models are under-utilized for Siamese lightweight tracking due to the com…
CPUGPUObject TrackingState Estimation+1Efficient Training for Visual Tracking with Deformable Transformer
Recent Transformer-based visual tracking models have showcased superior performance. Nevertheless, prior works have been resource-intensive, requiring prolonged GPU training hours and incurring high GFLOPs during inferen…
DecoderDenoisingGPUObject Tracking+2