Papers Multi-Object Tracking
“Multi-Object Tracking” 태그가 달린 논문 812편 · 필터 해제
Radar-Camera Fused Multi-Object Tracking: Online Calibration and Common Feature
This paper presents a Multi-Object Tracking (MOT) framework that fuses radar and camera data to enhance tracking efficiency while minimizing manual interventions. Contrary to many studies that underutilize radar and assi…
Multi-Object TrackingFutrTrack: A Camera-LiDAR Fusion Transformer for 3D Multiple Object Tracking
We propose FutrTrack, a modular camera-LiDAR multi-object tracking framework that builds on existing 3D detectors by introducing a transformer-based smoother and a fusion-driven tracker. Inspired by query-based tracking …
Multiple Object TrackingMulti-Object TrackingMonitoring Horses in Stalls: From Object to Event Detection
Monitoring the behavior of stalled horses is essential for early detection of health and welfare issues but remains labor-intensive and time-consuming. In this study, we present a prototype vision-based monitoring system…
Multi-Object TrackingObject DetectionEPIPTrack: Rethinking Prompt Modeling with Explicit and Implicit Prompts for Multi-Object Tracking
Multimodal semantic cues, such as textual descriptions, have shown strong potential in enhancing target perception for tracking. However, existing methods rely on static textual descriptions from large language models, w…
Multi-Object TrackingDMTrack: Deformable State-Space Modeling for UAV Multi-Object Tracking with Kalman Fusion and Uncertainty-Aware Association
Multi-object tracking (MOT) from unmanned aerial vehicles (UAVs) presents unique challenges due to unpredictable object motion, frequent occlusions, and limited appearance cues inherent to aerial viewpoints. These issues…
Multi-Object TrackingTrajectory ModelingMMOT: The First Challenging Benchmark for Drone-based Multispectral Multi-Object Tracking
Drone-based multi-object tracking is essential yet highly challenging due to small targets, severe occlusions, and cluttered backgrounds. Existing RGB-based tracking algorithms heavily depend on spatial appearance cues s…
Multi-Object TrackingGL-DT: Multi-UAV Detection and Tracking with Global-Local Integration
The extensive application of unmanned aerial vehicles (UAVs) in military reconnaissance, environmental monitoring, and related domains has created an urgent need for accurate and efficient multi-object tracking (MOT) tec…
Multi-Object TrackingFast Self-Supervised depth and mask aware Association for Multi-Object Tracking
Multi-object tracking (MOT) methods often rely on Intersection-over-Union (IoU) for association. However, this becomes unreliable when objects are similar or occluded. Also, computing IoU for segmentation masks is comput…
Multi-Object TrackingMotion-Aware Transformer for Multi-Object Tracking
Multi-object tracking (MOT) in videos remains challenging due to complex object motions and crowded scenes. Recent DETR-based frameworks offer end-to-end solutions but typically process detection and tracking queries joi…
Multi-Object TrackingInvestigating Traffic Accident Detection Using Multimodal Large Language Models
Traffic safety remains a critical global concern, with timely and accurate accident detection essential for hazard reduction and rapid emergency response. Infrastructure-based vision sensors offer scalable and efficient …
Traffic Accident DetectionMulti-Object TrackingInstance SegmentationObject DetectionDepTR-MOT: Unveiling the Potential of Depth-Informed Trajectory Refinement for Multi-Object Tracking
Visual Multi-Object Tracking (MOT) is a crucial component of robotic perception, yet existing Tracking-By-Detection (TBD) methods often rely on 2D cues, such as bounding boxes and motion modeling, which struggle under oc…
Multi-Object TrackingVSE-MOT: Multi-Object Tracking in Low-Quality Video Scenes Guided by Visual Semantic Enhancement
Current multi-object tracking (MOT) algorithms typically overlook issues inherent in low-quality videos, leading to significant degradation in tracking performance when confronted with real-world image deterioration. The…
Multi-Object TrackingReal-Time Detection and Tracking of Foreign Object Intrusions in Power Systems via Feature-Based Edge Intelligence
This paper presents a novel three-stage framework for real-time foreign object intrusion (FOI) detection and tracking in power transmission systems. The framework integrates: (1) a YOLOv7 segmentation model for fast and …
Multi-Object TrackingObject LocalizationMulti-animal tracking in Transition: Comparative Insights into Established and Emerging Methods
Precision livestock farming requires advanced monitoring tools to meet the increasing management needs of the industry. Computer vision systems capable of long-term multi-animal tracking (MAT) are essential for continuou…
Multi-Object TrackingMotion Estimation for Multi-Object Tracking using KalmanNet with Semantic-Independent Encoding
Motion estimation is a crucial component in multi-object tracking (MOT). It predicts the trajectory of objects by analyzing the changes in their positions in consecutive frames of images, reducing tracking failures and i…
Multi-Object TrackingAn HMM-based framework for identity-aware long-term multi-object tracking from sparse and uncertain identification: use case on long-term tracking in livestock
The need for long-term multi-object tracking (MOT) is growing due to the demand for analyzing individual behaviors in videos that span several minutes. Unfortunately, due to identity switches between objects, the trackin…
Multi-Object TrackingSparse BEV Fusion with Self-View Consistency for Multi-View Detection and Tracking
Multi-View Multi-Object Tracking (MVMOT) is essential for applications such as surveillance, autonomous driving, and sports analytics. However, maintaining consistent object identities across multiple cameras remains cha…
Multi-Object TrackingAutonomous DrivingObject DetectionDeepSea MOT: A benchmark dataset for multi-object tracking on deep-sea video
Benchmarking multi-object tracking and object detection model performance is an essential step in machine learning model development, as it allows researchers to evaluate model detection and tracker performance on human-…
Multi-Object TrackingObject DetectionSee No Evil: Adversarial Attacks Against Linguistic-Visual Association in Referring Multi-Object Tracking Systems
Language-vision understanding has driven the development of advanced perception systems, most notably the emerging paradigm of Referring Multi-Object Tracking (RMOT). By leveraging natural-language queries, RMOT systems …
Multi-Object TrackingSpatial ReasoningNOOUGAT: Towards Unified Online and Offline Multi-Object Tracking
The long-standing division between \textit{online} and \textit{offline} Multi-Object Tracking (MOT) has led to fragmented solutions that fail to address the flexible temporal requirements of real-world deployment scenari…
Multi-Object TrackingGraph Neural Network