Papers Object Tracking
“Object Tracking” 태그가 달린 논문 2,087편 · 필터 해제
CORT: Class-Oriented Real-time Tracking for Embedded Systems
The ever-increasing use of artificial intelligence in autonomous systems has significantly contributed to advance the research on multi-object tracking, adopted in several real-time applications (e.g., autonomous driving…
Autonomous DrivingMulti-Object TrackingObject TrackingTemporal Correlation Meets Embedding: Towards a 2nd Generation of JDE-based Real-Time Multi-Object Tracking
Joint Detection and Embedding (JDE) trackers have demonstrated excellent performance in Multi-Object Tracking (MOT) tasks by incorporating the extraction of appearance features as auxiliary tasks through embedding Re-Ide…
Multi-Object TrackingObject TrackingReal-Time Multi-Object TrackingOCTrack: Benchmarking the Open-Corpus Multi-Object Tracking
We study a novel yet practical problem of open-corpus multi-object tracking (OCMOT), which extends the MOT into localizing, associating, and recognizing generic-category objects of both seen (base) and unseen (novel) cla…
BenchmarkingMulti-Object TrackingObjectObject Recognition+1Boosting Online 3D Multi-Object Tracking through Camera-Radar Cross Check
In the domain of autonomous driving, the integration of multi-modal perception techniques based on data from diverse sensors has demonstrated substantial progress. Effectively surpassing the capabilities of state-of-the-…
3D Multi-Object TrackingAutonomous DrivingMulti-Object TrackingObject Tracking+1Strawberry detection and counting based on YOLOv7 pruning and information based tracking algorithm
The strawberry industry yields significant economic benefits for Florida, yet the process of monitoring strawberry growth and yield is labor-intensive and costly. The development of machine learning-based detection and t…
Multiple Object TrackingObjectObject TrackingMM-Tracker: Motion Mamba with Margin Loss for UAV-platform Multiple Object Tracking
Multiple object tracking (MOT) from unmanned aerial vehicle (UAV) platforms requires efficient motion modeling. This is because UAV-MOT faces both local object motion and global camera motion. Motion blur also increases …
MambaMultiple Object TrackingObject TrackingLost and Found: Overcoming Detector Failures in Online Multi-Object Tracking
Multi-object tracking (MOT) endeavors to precisely estimate the positions and identities of multiple objects over time. The prevailing approach, tracking-by-detection (TbD), first detects objects and then links detection…
Multi-Object TrackingObject TrackingOnline Multi-Object TrackingQuestion AnsweringDroneMOT: Drone-based Multi-Object Tracking Considering Detection Difficulties and Simultaneous Moving of Drones and Objects
Multi-object tracking (MOT) on static platforms, such as by surveillance cameras, has achieved significant progress, with various paradigms providing attractive performances. However, the effectiveness of traditional MOT…
Multi-Object TrackingObjectobject-detectionObject Detection+1Manipulating a Tetris-Inspired 3D Video Representation
Video Synopsis is a technique that performs video compression in a way that preserves the activity in the video. This technique is particularly useful in surveillance and monitoring applications. Although it is still a n…
Object TrackingVideo CompressionVideo SynopsisVisual Multi-Object Tracking with Re-Identification and Occlusion Handling using Labeled Random Finite Sets
This paper proposes an online visual multi-object tracking (MOT) algorithm that resolves object appearance-reappearance and occlusion. Our solution is based on the labeled random finite set (LRFS) filtering approach, whi…
Multi-Object TrackingObjectObject TrackingOcclusion HandlingCommRad: Context-Aware Sensing-Driven Millimeter-Wave Networks
Millimeter-wave (mmWave) technology is pivotal for next-generation wireless networks, enabling high-data-rate and low-latency applications such as autonomous vehicles and XR streaming. However, maintaining directional mm…
Autonomous VehiclesObject TrackingDeep Learning-Based Robust Multi-Object Tracking via Fusion of mmWave Radar and Camera Sensors
Autonomous driving holds great promise in addressing traffic safety concerns by leveraging artificial intelligence and sensor technology. Multi-Object Tracking plays a critical role in ensuring safer and more efficient n…
Autonomous Drivingmotion predictionMulti-Object TrackingObject TrackingGeoWATCH for Detecting Heavy Construction in Heterogeneous Time Series of Satellite Images
Learning from multiple sensors is challenging due to spatio-temporal misalignment and differences in resolution and captured spectra. To that end, we introduce GeoWATCH, a flexible framework for training models on long s…
Activity Recognitionimage-classificationImage ClassificationObject+4P2P: Part-to-Part Motion Cues Guide a Strong Tracking Framework for LiDAR Point Clouds
3D single object tracking (SOT) methods based on appearance matching has long suffered from insufficient appearance information incurred by incomplete, textureless and semantically deficient LiDAR point clouds. While mot…
3D Single Object TrackingGPUObject TrackingAddressing single object tracking in satellite imagery through prompt-engineered solutions
Object tracking in satellite videos remains a complex endeavor in remote sensing due to the intricate and dynamic nature of satellite imagery. Existing state-of-the-art trackers in computer vision integrate sophisticated…
ObjectObject TrackingPrompt EngineeringTF-SASM: Training-free Spatial-aware Sparse Memory for Multi-object Tracking
Multi-object tracking (MOT) in computer vision remains a significant challenge, requiring precise localization and continuous tracking of multiple objects in video sequences. The emergence of data sets that emphasize rob…
Multi-Object TrackingObjectObject TrackingSSP-GNN: Learning to Track via Bilevel Optimization
We propose a graph-based tracking formulation for multi-object tracking (MOT) where target detections contain kinematic information and re-identification features (attributes). Our method applies a successive shortest pa…
Bilevel OptimizationGraph Neural NetworkMulti-Object TrackingObject TrackingFeatureSORT: Essential Features for Effective Tracking
In this work, we introduce a novel tracker designed for online multiple object tracking with a focus on being simple, while being effective. we provide multiple feature modules each of which stands for a particular appea…
Multi-Object TrackingMultiple Object TrackingObject TrackingOcclusion HandlingAttention Normalization Impacts Cardinality Generalization in Slot Attention
Object-centric scene decompositions are important representations for downstream tasks in fields such as computer vision and robotics. The recently proposed Slot Attention module, already leveraged by several derivative …
Image SegmentationObjectObject TrackingSemantic Segmentation+1TrackPGD: Efficient Adversarial Attack using Object Binary Masks against Robust Transformer Trackers
Adversarial perturbations can deceive neural networks by adding small, imperceptible noise to the input. Recent object trackers with transformer backbones have shown strong performance on tracking datasets, but their adv…
Adversarial AttackAdversarial RobustnessObjectObject Tracking+1