Papers Visual Tracking
“Visual Tracking” 태그가 달린 논문 581편 · 필터 해제
Multi-task Learning for Joint Re-identification, Team Affiliation, and Role Classification for Sports Visual Tracking
Effective tracking and re-identification of players is essential for analyzing soccer videos. But, it is a challenging task due to the non-linear motion of players, the similarity in appearance of players from the same t…
Multi-Task LearningVisual TrackingExplicit 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 TrackingAutoregressive Queries for Adaptive Tracking with Spatio-Temporal Transformers
The rich spatio-temporal information is crucial to capture the complicated target appearance variations in visual tracking. However most top-performing tracking algorithms rely on many hand-crafted components for spa…
Visual 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 TrackingCross-Modal Object Tracking via Modality-Aware Fusion Network and A Large-Scale Dataset
Visual tracking often faces challenges such as invalid targets and decreased performance in low-light conditions when relying solely on RGB image sequences. While incorporating additional modalities like depth and infrar…
Object TrackingVisual TrackingVisual tracking brain computer interface
Brain-computer interfaces (BCIs) offer a way to interact with computers without relying on physical movements. Non-invasive electroencephalography (EEG)-based visual BCIs, known for efficient speed and calibration ease, …
Brain Computer Interfacecontinuous-controlContinuous ControlEEG+1HIPTrack: 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 TrackingZoomTrack: Target-aware Non-uniform Resizing for Efficient Visual Tracking
Recently, the transformer has enabled the speed-oriented trackers to approach state-of-the-art (SOTA) performance with high-speed thanks to the smaller input size or the lighter feature extraction backbone, though they s…
Visual TrackingStaged Depthwise Correlation and Feature Fusion for Siamese Object Tracking
In this work, we propose a novel staged depthwise correlation and feature fusion network, named DCFFNet, to further optimize the feature extraction for visual tracking. We build our deep tracker upon a siamese network ar…
Object TrackingVisual TrackingEvent 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+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+1LiteTrack: Layer Pruning with Asynchronous Feature Extraction for Lightweight and Efficient Visual Tracking
The recent advancements in transformer-based visual trackers have led to significant progress, attributed to their strong modeling capabilities. However, as performance improves, running latency correspondingly increases…
GPUVisual TrackingEfficient 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+2Towards Efficient Training with Negative Samples in Visual Tracking
Current state-of-the-art (SOTA) methods in visual object tracking often require extensive computational resources and vast amounts of training data, leading to a risk of overfitting. This study introduces a more efficien…
Object TrackingVisual Object TrackingVisual TrackingRobust Visual Tracking by Motion Analyzing
In recent years, Video Object Segmentation (VOS) has emerged as a complementary method to Video Object Tracking (VOT). VOS focuses on classifying all the pixels around the target, allowing for precise shape labeling, whi…
Object TrackingSegmentationSemantic SegmentationTensor Decomposition+4Improving Underwater Visual Tracking With a Large Scale Dataset and Image Enhancement
This paper presents a new dataset and general tracker enhancement method for Underwater Visual Object Tracking (UVOT). Despite its significance, underwater tracking has remained unexplored due to data inaccessibility. It…
Image EnhancementObject TrackingVisual Object TrackingVisual TrackingLearning Visual Tracking and Reaching with Deep Reinforcement Learning on a UR10e Robotic Arm
As technology progresses, industrial and scientific robots are increasingly being used in diverse settings. In many cases, however, programming the robot to perform such tasks is technically complex and costly. To maximi…
Deep Reinforcement LearningQ-Learningreinforcement-learningReinforcement Learning+1Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and Segmentation
Tracking any given object(s) spatially and temporally is a common purpose in Visual Object Tracking (VOT) and Video Object Segmentation (VOS). Joint tracking and segmentation have been attempted in some studies but they …
ObjectObject TrackingRepresentation LearningSegmentation+5