Papers Multi-Object Tracking
“Multi-Object Tracking” 태그가 달린 논문 812편 · 필터 해제
PKF: Probabilistic Data Association Kalman Filter for Multi-Object Tracking
In this paper, we derive a new Kalman filter with probabilistic data association between measurements and states. We formulate a variational inference problem to approximate the posterior density of the state conditioned…
CPUMulti-Object TrackingObject TrackingVariational InferenceMulti-object Tracking by Detection and Query: an efficient end-to-end manner
Multi-object tracking is advancing through two dominant paradigms: traditional tracking by detection and newly emerging tracking by query. In this work, we fuse them together and propose the tracking-by-detection-and-que…
Multi-Object TrackingObject TrackingGraph-Based Multi-Modal Sensor Fusion for Autonomous Driving
The growing demand for robust scene understanding in mobile robotics and autonomous driving has highlighted the importance of integrating multiple sensing modalities. By combining data from diverse sensors like cameras a…
Autonomous DrivingMulti-Object TrackingObject TrackingScene Understanding+2HopTrack: A Real-time Multi-Object Tracking System for Embedded Devices
Multi-Object Tracking (MOT) poses significant challenges in computer vision. Despite its wide application in robotics, autonomous driving, and smart manufacturing, there is limited literature addressing the specific chal…
Autonomous DrivingGPUMulti-Object TrackingObject Tracking+1IP-MOT: Instance Prompt Learning for Cross-Domain Multi-Object Tracking
Multi-Object Tracking (MOT) aims to associate multiple objects across video frames and is a challenging vision task due to inherent complexities in the tracking environment. Most existing approaches train and track withi…
Knowledge DistillationLanguage ModellingMulti-Object TrackingObject Tracking+2SFTrack: A Robust Scale and Motion Adaptive Algorithm for Tracking Small and Fast Moving Objects
This paper addresses the problem of multi-object tracking in Unmanned Aerial Vehicle (UAV) footage. It plays a critical role in various UAV applications, including traffic monitoring systems and real-time suspect trackin…
BenchmarkingMulti-Object TrackingObject TrackingOVT-B: A New Large-Scale Benchmark for Open-Vocabulary Multi-Object Tracking
Open-vocabulary object perception has become an important topic in artificial intelligence, which aims to identify objects with novel classes that have not been seen during training. Under this setting, open-vocabulary o…
Multi-Object TrackingObjectobject-detectionObject Detection+3MPT: A Large-scale Multi-Phytoplankton Tracking Benchmark
Phytoplankton are a crucial component of aquatic ecosystems, and effective monitoring of them can provide valuable insights into ocean environments and ecosystem changes. Traditional phytoplankton monitoring methods are …
Multi-Object TrackingObject Tracking3D Multi-Object Tracking Employing MS-GLMB Filter for Autonomous Driving
The MS-GLMB filter offers a robust framework for tracking multiple objects through the use of multi-sensor data. Building on this, the MV-GLMB and MV-GLMB-AB filters enhance the MS-GLMB capabilities by employing cameras …
3D Multi-Object TrackingAutonomous DrivingMulti-Object TrackingObject+1Temporal-Enhanced Multimodal Transformer for Referring Multi-Object Tracking and Segmentation
Referring multi-object tracking (RMOT) is an emerging cross-modal task that aims to locate an arbitrary number of target objects and maintain their identities referred by a language expression in a video. This intricate …
Multi-Object TrackingMulti-Object Tracking and SegmentationObject TrackingReferring Multi-Object Tracking+3Motion-guided small MAV detection in complex and non-planar scenes
In recent years, there has been a growing interest in the visual detection of micro aerial vehicles (MAVs) due to its importance in numerous applications. However, the existing methods based on either appearance or motio…
Multi-Object TrackingObject TrackingEfficient Multi-Object Tracking on Edge Devices via Reconstruction-Based Channel Pruning
The advancement of multi-object tracking (MOT) technologies presents the dual challenge of maintaining high performance while addressing critical security and privacy concerns. In applications such as pedestrian tracking…
Edge-computingMulti-Object TrackingNetwork PruningObject TrackingVOVTrack: Exploring the Potentiality in Videos for Open-Vocabulary Object Tracking
Open-vocabulary multi-object tracking (OVMOT) represents a critical new challenge involving the detection and tracking of diverse object categories in videos, encompassing both seen categories (base classes) and unseen c…
Multi-Object TrackingObjectobject-detectionObject Detection+4Enhanced Kalman with Adaptive Appearance Motion SORT for Grounded Generic Multiple Object Tracking
Despite recent progress, Multi-Object Tracking (MOT) continues to face significant challenges, particularly its dependence on prior knowledge and predefined categories, complicating the tracking of unfamiliar objects. Ge…
Multi-Object TrackingMultiple Object TrackingObject TrackingSpatial-Temporal Multi-Cuts for Online Multiple-Camera Vehicle Tracking
Accurate online multiple-camera vehicle tracking is essential for intelligent transportation systems, autonomous driving, and smart city applications. Like single-camera multiple-object tracking, it is commonly formulate…
Autonomous DrivingMulti-Object TrackingMultiple Object TrackingObject TrackingOpen3DTrack: Towards Open-Vocabulary 3D Multi-Object Tracking
3D multi-object tracking plays a critical role in autonomous driving by enabling the real-time monitoring and prediction of multiple objects' movements. Traditional 3D tracking systems are typically constrained by predef…
3D Multi-Object TrackingAutonomous DrivingMulti-Object TrackingObject+1VETRA: A Dataset for Vehicle Tracking in Aerial Imagery - New Challenges for Multi-Object Tracking
The informative power of traffic analysis can be enhanced by considering changes in both time and space. Vehicle tracking algorithms applied to drone videos provide a better overview than street-level surveillance camera…
de-enMotion CompensationMulti-Object TrackingObject TrackingAn Overview of Multi-Object Estimation via Labeled Random Finite Set
This article presents the Labeled Random Finite Set (LRFS) framework for multi-object systems-systems in which the number of objects and their states are unknown and vary randomly with time. In particular, we focus on st…
Multi-Object TrackingObjectObject TrackingAdapTrack: Adaptive Thresholding-Based Matching For Multi-object Tracking
Multi-object tracking (MOT) plays a pivotal role in various computer vision domains with recent tracking-by detection algorithms that treat MOT as distinct detection and association tasks. However, the existing trackers …
Multi-Object TrackingObject TrackingA Confidence-Aware Matching Strategy For Generalized Multi-Object Tracking
Multi-object tracking (MOT), a crucial task in computer vision, has broad applicability, and recently, tracking-by-detection-based trackers, which separate the processes of object detection and association, are showing s…
Multi-Object Trackingobject-detectionObject DetectionObject Tracking