Papers Multi-Object Tracking
“Multi-Object Tracking” 태그가 달린 논문 812편 · 필터 해제
ByteTraX: Enhancing the ByteTrack Architecture with Optimised Thresholding
The ByteTrack algorithm is a widely used and computationally efficient multi-object tracking architecture. Its core innovation lies in the combination of lenient bounding box associations with tracklet similarity matchin…
Multi-Object TrackingObject DetectionTracking the Unseen: An Occlusion-Robust Framework for Target Tracking Under Full and Long-Term Occlusion
Real-time multi-object tracking systems remain highly vulnerable to full and long-term occlusion, where targets temporarily or completely disappear from the camera's field of view. Conventional trackers may terminate tra…
Multiple Object TrackingMulti-Object TrackingObject DetectionTeach a Molmo2Fish: Towards interactive fish tracking with natural language guidance
Computer vision is increasingly used to automate recognition tasks in large ecological datasets, but more complex tasks such as multi-object tracking continue to pose challenges. As researchers seek to incorporate vision…
Multi-Object TrackingProbing Association Instability with Track-State Perturbations for Clip-Level Active Learning in Query-Propagation Multi-Object Tracking
Training query-propagation end-to-end multi-object tracking (MOT) models requires dense bounding-box and identity annotations across video sequences, making dataset construction expensive. Clip-level active learning redu…
Multi-Object TrackingActive LearningCD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking
Referring multi-object tracking (RMOT) extends tracking from category-driven perception to language-guided understanding by grounding object trajectories in natural-language expressions. Despite recent progress, existing…
Multi-Object TrackingObject DetectionIncremental Optimal Assignment for Real-Time Crowd Tracking
Multi-object tracking in dense crowds requires solving a bipartite assignment problem between detections and trajectories at every video frame. The classical Hungarian algorithm solves this in $O(N^3)$ time, which become…
Multi-Object TrackingSpikingMOT: A Spike-Driven Multi-Object Tracker
Multi-object tracking (MOT) plays a fundamental role in visual perception, where accurate trajectory prediction is essential for reliable target association under complex motion patterns. Recent trackers have improved mo…
Multi-Object TrackingTrajectory PredictionREMIND: RE-Identification with Memory for INDoor Navigation
Mobile robots operating indoors must re-identify previously observed objects after long temporal gaps, significant viewpoint changes, and severe illumination variations. This remains a challenging problem: multi-object t…
Video Object SegmentationVehicle Re-IdentificationMulti-Object TrackingWaspMOT: A Benchmark for Long-Term Multi-Object Tracking of Trichogramma Wasps
Multi-object tracking (MOT) has achieved strong performance on benchmarks dominated by short video sequences. However, such datasets do not adequately evaluate long-term identity preservation, where objects must be track…
Multi-Object TrackingAnswer Set Programming Energised! End-to-End Neurosymbolic Reasoning and Learning with ASP and Energy Based Models
We present a general neurosymbolic reasoning and learning methodology based on a modular integration of answer set programming with an energy based model substrate. Key contributions are: (1) supporting joint optimisatio…
Multi-Object TrackingHieDG: A Hierarchical Discrete Geometry-Guided Framework for Multi-Animal Tracking
Multi-animal tracking (MAT) is critical for wildlife monitoring and behavioral analysis, yet remains challenging due to uniform appearance, high density, and irregular motion. Existing methods typically follow heuristic-…
Multi-Object TrackingCylindTrack: Depth-Aware Cylindrical Motion Modeling for Panoramic Multi-Object Tracking
Multi-Object Tracking (MOT) is a core capability for embodied perception, and panoramic cameras are attractive for embodied systems because their 360° field of view reduces blind spots and keeps surrounding targets obser…
Multi-Object TrackingTrajectory ModelingPS-MOT: Cultivating Instance Awareness from Point Seeds for Multi-Object Tracking
We introduce Point-supervised Multi-Object Tracking (PS-MOT) as a cost-effective alternative to traditional bounding box supervision, shifting the focus from spatial fitting to topological center-driven representation. H…
Multi-Object TrackingPolycepta: Object-Centric Appearance Estimation for Multi-Object Tracking
The tracking-by-detection paradigm in multi-object tracking (MOT) typically relies on static appearance descriptors to complement motion estimation. However, these descriptors are frame-independent, limiting their robust…
Multi-Object TrackingTowards Accurate and Robust Surveillance Roadside IVD via Trackletized Audio-Visual Reasoning
Idling Vehicle Detection (IVD) seeks to determine, at the final frame of a video clip, whether any vehicle is idling, meaning the vehicle is stationary with its engine running, using synchronized video from a remote surv…
Multi-Object TrackingVisual ReasoningARGUSTRACK: A Multi-View Annotation System for Multi-Object Tracking
Multi-Camera Multi-Target (MCMT) tracking has emerged as a critical capability for applications ranging from autonomous driving to animal behavior monitoring. While recent advances have yielded sophisticated tracking alg…
Multi-Object TrackingAutonomous DrivingFEMOT: Multi-Object Tracking using Frame and Event Cameras
Conventional RGB cameras have been widely used in multi-object tracking due to their ability to capture rich appearance and semantic information. However, their performance is often degraded under complex real-world chal…
Multi-Object TrackingObject LocalizationKATANA: A Fast, Low-Power Mapping of Kalman Filters onto Edge NPUs for Real-Time Tracking
State estimation is the closed-loop core of every real-time tracking system, from radar surveillance and counter-UAV defense to autonomous driving and robotics. These deployments run on edge platforms, where defense syst…
Multi-Object TrackingAutonomous DrivingSelective Mask Propagation for Multi-Object Tracking
In multi-object tracking, most frames are easy for a lightweight base tracker while a small fraction is intrinsically hard. Video object segmentation (VOS) models can often preserve identity through the hard frames where…
Video Object SegmentationMulti-Object TrackingHDST-GNN: Heterogeneous Dynamic Spatiotemporal Graph Neural Networks for Multi-Object Tracking in UAV Aerial Imagery
Multi-object tracking (MOT) from UAV imagery presents unique challenges: altitude varies across sequences, objects are small and densely packed, and frequent occlusion causes identity switches. Existing graph-based track…
Multi-Object TrackingGraph Neural Network