Papers Multi-Object Tracking
“Multi-Object Tracking” 태그가 달린 논문 812편 · 필터 해제
Cross-View Referring Multi-Object Tracking
Referring Multi-Object Tracking (RMOT) is an important topic in the current tracking field. Its task form is to guide the tracker to track objects that match the language description. Current research mainly focuses on r…
Cross-view Referring Multi-Object TrackingMulti-Object TrackingObjectObject Tracking+1Tell Me What to Track: Infusing Robust Language Guidance for Enhanced Referring Multi-Object Tracking
Referring multi-object tracking (RMOT) is an emerging cross-modal task that aims to localize an arbitrary number of targets based on a language expression and continuously track them in a video. This intricate task invol…
DecoderMulti-Object TrackingObject TrackingReferring Multi-Object TrackingHeterogeneous Graph Transformer for Multiple Tiny Object Tracking in RGB-T Videos
Tracking multiple tiny objects is highly challenging due to their weak appearance and limited features. Existing multi-object tracking algorithms generally focus on single-modality scenes, and overlook the complementary …
Multi-Object TrackingMultiple Object TrackingObjectObject TrackingTGOSPA Metric Parameters Selection and Evaluation for Visual Multi-object Tracking
Multi-object tracking algorithms are deployed in various applications, each with unique performance requirements. For example, track switches pose significant challenges for offline scene understanding, as they hinder th…
Multi-Object TrackingObject TrackingScene UnderstandingPost-Hoc MOTS: Exploring the Capabilities of Time-Symmetric Multi-Object Tracking
Temporal forward-tracking has been the dominant approach for multi-object segmentation and tracking (MOTS). However, a novel time-symmetric tracking methodology has recently been introduced for the detection, segmentatio…
Multi-Object TrackingObject TrackingSemantic SegmentationEnhanced Multi-Object Tracking Using Pose-based Virtual Markers in 3x3 Basketball
Multi-object tracking (MOT) is crucial for various multi-agent analyses such as evaluating team sports tactics and player movements and performance. While pedestrian tracking has advanced with Tracking-by-Detection MOT, …
Active LearningMulti-Object TrackingObject TrackingBeyond Boxes: Mask-Guided Spatio-Temporal Feature Aggregation for Video Object Detection
The primary challenge in Video Object Detection (VOD) is effectively exploiting temporal information to enhance object representations. Traditional strategies, such as aggregating region proposals, often suffer from feat…
GPUMulti-Object TrackingObjectobject-detection+4Eyes on the Road: State-of-the-Art Video Question Answering Models Assessment for Traffic Monitoring Tasks
Recent advances in video question answering (VideoQA) offer promising applications, especially in traffic monitoring, where efficient video interpretation is critical. Within ITS, answering complex, real-time queries lik…
Multi-Object TrackingObject TrackingQuestion AnsweringVideo Question AnsweringMCBLT: Multi-Camera Multi-Object 3D Tracking in Long Videos
Object perception from multi-view cameras is crucial for intelligent systems, particularly in indoor environments, e.g., warehouses, retail stores, and hospitals. Most traditional multi-target multi-camera (MTMC) detecti…
2D Object Detection3D Object DetectionCamera CalibrationMulti-Object Tracking+4Visual SLAMMOT Considering Multiple Motion Models
Simultaneous Localization and Mapping (SLAM) and Multi-Object Tracking (MOT) are pivotal tasks in the realm of autonomous driving, attracting considerable research attention. While SLAM endeavors to generate real-time ma…
Autonomous DrivingMulti-Object TrackingObject TrackingSimultaneous Localization and MappingCrossTracker: Robust Multi-modal 3D Multi-Object Tracking via Cross Correction
The fusion of camera- and LiDAR-based detections offers a promising solution to mitigate tracking failures in 3D multi-object tracking (MOT). However, existing methods predominantly exploit camera detections to correct t…
3D Multi-Object TrackingMulti-Object TrackingObject TrackingFastTrackTr:Towards Fast Multi-Object Tracking with Transformers
Transformer-based multi-object tracking (MOT) methods have captured the attention of many researchers in recent years. However, these models often suffer from slow inference speeds due to their structure or other issues.…
Multi-Object TrackingObjectObject TrackingLearning a Neural Association Network for Self-supervised Multi-Object Tracking
This paper introduces a novel framework to learn data association for multi-object tracking in a self-supervised manner. Fully-supervised learning methods are known to achieve excellent tracking performances, but acquiri…
Multi-Object TrackingObject TrackingMOT FCG++: Enhanced Representation of Spatio-temporal Motion and Appearance Features
The goal of multi-object tracking (MOT) is to detect and track all objects in a scene across frames, while maintaining a unique identity for each object. Most existing methods rely on the spatial-temporal motion features…
Multi-Object TrackingObject TrackingState Estimation3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter
3D Multi-Object Tracking (MOT), a fundamental component of environmental perception, is essential for intelligent systems like autonomous driving and robotic sensing. Although Tracking-by-Detection frameworks have demons…
3D Multi-Object TrackingAutonomous DrivingMulti-Object TrackingObject+1DEEGITS: Deep Learning based Framework for Measuring Heterogenous Traffic State in Challenging Traffic Scenarios
This paper presents DEEGITS (Deep Learning Based Heterogeneous Traffic State Measurement), a comprehensive framework that leverages state-of-the-art convolutional neural network (CNN) techniques to accurately and rapidly…
Multi-Object TrackingObject TrackingTransfer LearningGTA: Global Tracklet Association for Multi-Object Tracking in Sports
Multi-object tracking in sports scenarios has become one of the focal points in computer vision, experiencing significant advancements through the integration of deep learning techniques. Despite these breakthroughs, cha…
Multi-Object TrackingMultiple Object TrackingObject TrackingBuckTales : A multi-UAV dataset for multi-object tracking and re-identification of wild antelopes
Understanding animal behaviour is central to predicting, understanding, and mitigating impacts of natural and anthropogenic changes on animal populations and ecosystems. However, the challenges of acquiring and processin…
BenchmarkingMulti-Object TrackingObject TrackingSynCL: A Synergistic Training Strategy with Instance-Aware Contrastive Learning for End-to-End Multi-Camera 3D Tracking
While existing query-based 3D end-to-end visual trackers integrate detection and tracking via the tracking-by-attention paradigm, these two chicken-and-egg tasks encounter optimization difficulties when sharing the same …
3D Multi-Object TrackingContrastive LearningDecoderMulti-Object Tracking+3Track Any Peppers: Weakly Supervised Sweet Pepper Tracking Using VLMs
In the Detection and Multi-Object Tracking of Sweet Peppers Challenge, we present Track Any Peppers (TAP) - a weakly supervised ensemble technique for sweet peppers tracking. TAP leverages the zero-shot detection capabil…
Multi-Object TrackingObjectobject-detectionObject Detection+1