Papers Multi-Object Tracking
“Multi-Object Tracking” 태그가 달린 논문 812편 · 필터 해제
BrackishMOT: The Brackish Multi-Object Tracking Dataset
There exist no publicly available annotated underwater multi-object tracking (MOT) datasets captured in turbid environments. To remedy this we propose the BrackishMOT dataset with focus on tracking schools of small fish,…
Multi-Object TrackingObjectObject TrackingSelf-Supervised Representation Learning from Temporal Ordering of Automated Driving Sequences
Self-supervised feature learning enables perception systems to benefit from the vast raw data recorded by vehicle fleets worldwide. While video-level self-supervised learning approaches have shown strong generalizability…
Multi-Object TrackingObjectobject-detectionObject Detection+4DIVOTrack: A Novel Dataset and Baseline Method for Cross-View Multi-Object Tracking in DIVerse Open Scenes
Cross-view multi-object tracking aims to link objects between frames and camera views with substantial overlaps. Although cross-view multi-object tracking has received increased attention in recent years, existing datase…
Multi-Object TrackingObjectobject-detectionObject Detection+1Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Tracking
This work proposes an end-to-end multi-camera 3D multi-object tracking (MOT) framework. It emphasizes spatio-temporal continuity and integrates both past and future reasoning for tracked objects. Thus, we name it "Past-a…
3D Multi-Object TrackingMulti-Object TrackingObjectObject TrackingSelf-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction
We introduce a novel robotic system for improving unseen object instance segmentation in the real world by leveraging long-term robot interaction with objects. Previous approaches either grasp or push an object and then …
Instance SegmentationMulti-Object TrackingObjectObject Tracking+6An Efficient Semi-Automated Scheme for Infrastructure LiDAR Annotation
Most existing perception systems rely on sensory data acquired from cameras, which perform poorly in low light and adverse weather conditions. To resolve this limitation, we have witnessed advanced LiDAR sensors become p…
Autonomous DrivingMulti-Object TrackingObjectobject-detection+3Tracking Different Ant Species: An Unsupervised Domain Adaptation Framework and a Dataset for Multi-object Tracking
Tracking individuals is a vital part of many experiments conducted to understand collective behaviour. Ants are the paradigmatic model system for such experiments but their lack of individually distinguishing visual feat…
Domain AdaptationMulti-Object TrackingObject TrackingUnsupervised Domain AdaptationTracking Multiple Deformable Objects in Egocentric Videos
Most existing multiple object tracking (MOT) methods that solely rely on appearance features struggle in tracking highly deformable objects. Other MOT methods that use motion clues to associate identities across fram…
DisentanglementMotion DisentanglementMulti-Object TrackingMultiple Object Tracking+1Context-Aware Relative Object Queries To Unify Video Instance and Panoptic Segmentation
Object queries have emerged as a powerful abstraction to generically represent object proposals. However, their use for temporal tasks like video segmentation poses two questions: 1) How to process frames sequentiall…
Instance SegmentationMulti-Object TrackingMulti-Object Tracking and SegmentationObject+9Heterogeneous Diversity Driven Active Learning for Multi-Object Tracking
The existing one-stage multi-object tracking (MOT) algorithms have achieved satisfactory performance benefiting from a large amount of labeled data. However, acquiring plenty of laborious annotated frames is not prac…
Active LearningDiversityMulti-Object TrackingObject TrackingEnd-to-end 3D Tracking with Decoupled Queries
In this work, we present an end-to-end framework for camera-based 3D multi-object tracking, called DQTrack. To avoid heuristic design in detection-based trackers, recent query-based approaches deal with identity-agno…
3D Multi-Object TrackingMulti-Object TrackingObject TrackingA Fast Unified System for 3D Object Detection and Tracking
We present FUS3D, a fast and lightweight system for real-time 3D object detection and tracking on edge devices. Our approach seamlessly integrates stages for 3D object detection and multi-object-tracking into a singl…
3D Object DetectionMulti-Object TrackingObjectobject-detection+2F&F Attack: Adversarial Attack against Multiple Object Trackers by Inducing False Negatives and False Positives
Multi-object tracking (MOT) aims to build moving trajectories for number-agnostic objects. Modern multi-object trackers commonly follow the tracking-by-detection strategy. Therefore, fooling detectors can be an effec…
Adversarial AttackMulti-Object TrackingObjectObject TrackingTracking Passengers and Baggage Items using Multiple Overhead Cameras at Security Checkpoints
We introduce a novel framework to track multiple objects in overhead camera videos for airport checkpoint security scenarios where targets correspond to passengers and their baggage items. We propose a Self-Supervised Le…
Data AugmentationInstance SegmentationMulti-Object TrackingObject+6Tracking by Associating Clips
The tracking-by-detection paradigm today has become the dominant method for multi-object tracking and works by detecting objects in each frame and then performing data association across frames. However, its sequential f…
ChunkingManagementMulti-Object TrackingObject+1Neural Enhanced Belief Propagation for Multiobject Tracking
Algorithmic solutions for multi-object tracking (MOT) are a key enabler for applications in autonomous navigation and applied ocean sciences. State-of-the-art MOT methods fully rely on a statistical model and typically u…
Autonomous DrivingAutonomous NavigationMulti-Object TrackingObject TrackingDetection-aware multi-object tracking evaluation
How would you fairly evaluate two multi-object tracking algorithms (i.e. trackers), each one employing a different object detector? Detectors keep improving, thus trackers can make less effort to estimate object states o…
Multi-Object TrackingObjectObject TrackingJoint Counting, Detection and Re-Identification for Multi-Object Tracking
The recent trend in 2D multiple object tracking (MOT) is jointly solving detection and tracking, where object detection and appearance feature (or motion) are learned simultaneously. Despite competitive performance, in c…
Multi-Object TrackingMultiple Object TrackingObjectobject-detection+2Multiple Object Tracking Challenge Technical Report for Team MT_IoT
This is a brief technical report of our proposed method for Multiple-Object Tracking (MOT) Challenge in Complex Environments. In this paper, we treat the MOT task as a two-stage task including human detection and traject…
Human DetectionMulti-Object TrackingObjectObject Tracking+1Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation
Although existing multi-object tracking (MOT) algorithms have obtained competitive performance on various benchmarks, almost all of them train and validate models on the same domain. The domain generalization problem of …
Domain GeneralizationMulti-Object TrackingMultiple Object TrackingObject Tracking