SOTAVerified

Object Tracking

Object tracking is the task of taking an initial set of object detections, creating a unique ID for each of the initial detections, and then tracking each of the objects as they move around frames in a video, maintaining the ID assignment. State-of-the-art methods involve fusing data from RGB and event-based cameras to produce more reliable object tracking. CNN-based models using only RGB images as input are also effective. The most popular benchmark is OTB. There are several evaluation metrics specific to object tracking, including HOTA, MOTA, IDF1, and Track-mAP.

( Image credit: Towards-Realtime-MOT )

Papers

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Showing 201–250 of 1966 papers

TitleStatusHype
3D Multi-Object Tracking Employing MS-GLMB Filter for Autonomous DrivingCode0
Enhancing In-vehicle Multiple Object Tracking Systems with Embeddable Ising Machines—0
Temporal-Enhanced Multimodal Transformer for Referring Multi-Object Tracking and Segmentation—0
UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles—0
Motion-guided small MAV detection in complex and non-planar scenes—0
DINTR: Tracking via Diffusion-based Interpolation—0
Enhanced Kalman with Adaptive Appearance Motion SORT for Grounded Generic Multiple Object Tracking—0
VOVTrack: Exploring the Potentiality in Videos for Open-Vocabulary Object Tracking—0
VideoSAM: Open-World Video Segmentation—0
Efficient Multi-Object Tracking on Edge Devices via Reconstruction-Based Channel Pruning—0
Automated Retail Billing: Streamlining Checkout with QR Codes and Object Tracking Using YOLOv8 and DeepSORTCode0
Spiking Neural Network as Adaptive Event Stream SlicerCode1
DTVLT: A Multi-modal Diverse Text Benchmark for Visual Language Tracking Based on LLM—0
Spatial-Temporal Multi-Cuts for Online Multiple-Camera Vehicle TrackingCode1
Tracking objects that change in appearance with phase synchrony—0
Samba: Synchronized Set-of-Sequences Modeling for Multiple Object Tracking—0
Open3DTrack: Towards Open-Vocabulary 3D Multi-Object TrackingCode1
VETRA: A Dataset for Vehicle Tracking in Aerial Imagery - New Challenges for Multi-Object Tracking—0
One Token to Seg Them All: Language Instructed Reasoning Segmentation in VideosCode2
A Confidence-Aware Matching Strategy For Generalized Multi-Object TrackingCode1
AdapTrack: Adaptive Thresholding-Based Matching For Multi-object TrackingCode1
An Overview of Multi-Object Estimation via Labeled Random Finite Set—0
Improving Visual Object Tracking through Visual PromptingCode1
BlinkTrack: Feature Tracking over 100 FPS via Events and Images—0
CAMOT: Camera Angle-aware Multi-Object Tracking—0
General Compression Framework for Efficient Transformer Object Tracking—0
Walker: Self-supervised Multiple Object Tracking by Walking on Temporal Appearance Graphs—0
Underwater Camouflaged Object Tracking Meets Vision-Language SAM2Code5
Automated Surgical Skill Assessment in Endoscopic Pituitary Surgery using Real-time Instrument Tracking on a High-fidelity Bench-top Phantom—0
Progressive Representation Learning for Real-Time UAV TrackingCode2
Enhancing Nighttime UAV Tracking with Light Distribution SuppressionCode1
CloudTrack: Scalable UAV Tracking with Cloud SemanticsCode1
MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous DrivingCode3
TrackNetV4: Enhancing Fast Sports Object Tracking with Motion Attention Maps—0
Masks and Boxes: Combining the Best of Both Worlds for Multi-Object Tracking—0
RockTrack: A 3D Robust Multi-Camera-Ken Multi-Object Tracking FrameworkCode2
SLAck: Semantic, Location, and Appearance Aware Open-Vocabulary TrackingCode1
STCMOT: Spatio-Temporal Cohesion Learning for UAV-Based Multiple Object TrackingCode1
Tracking Virtual Meetings in the Wild: Re-identification in Multi-Participant Virtual Meetings—0
Associate Everything Detected: Facilitating Tracking-by-Detection to the UnknownCode1
FACT: Feature Adaptive Continual-learning Tracker for Multiple Object Tracking—0
When to Extract ReID Features: A Selective Approach for Improved Multiple Object TrackingCode1
A Low-Computational Video Synopsis Framework with a Standard DatasetCode0
RCBEVDet++: Toward High-accuracy Radar-Camera Fusion 3D Perception Network—0
LITE: A Paradigm Shift in Multi-Object Tracking with Efficient ReID Feature IntegrationCode1
Gr-IoU: Ground-Intersection over Union for Robust Multi-Object Tracking with 3D Geometric Constraints—0
TP-GMOT: Tracking Generic Multiple Object by Textual Prompt with Motion-Appearance Cost (MAC) SORTCode0
YOLOO: You Only Learn from Others Once—0
TrackSSM: A General Motion Predictor by State-Space ModelCode1
UTrack: Multi-Object Tracking with Uncertain DetectionsCode2
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All datasetsCOESOTFE108QuadTrackSeaDronesSeeBIRDSAI - ICVGIP 2020KITTIMMPTRACKPerception TestVisEvent

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HR-CEUTrack-LargeSuccess Rate65—Unverified
2HR-CEUTrack-BaseSuccess Rate63.2—Unverified
3CEUTrack-LargeSuccess Rate62.8—Unverified
4CEUTrack-BaseSuccess Rate62—Unverified
5SiamR-CNNSuccess Rate60.9—Unverified
6TransTSuccess Rate60.5—Unverified
7SuperDiMPSuccess Rate60.2—Unverified
8TrDiMPSuccess Rate60.1—Unverified
9KeepTrackSuccess Rate59.6—Unverified
10AiATrackSuccess Rate59—Unverified
#ModelMetricClaimedVerifiedStatus
1HR-MonTrack-BaseSuccess Rate68.5—Unverified
2HR-MonTrack-TinySuccess Rate66.3—Unverified
3Multi-modalSuccess Rate63.4—Unverified
4PrDiMPSuccess Rate59—Unverified
5DiMPSuccess Rate57.1—Unverified
6MonTrackSuccess Rate54.9—Unverified
7ATOMSuccess Rate46.5—Unverified
8KYSSuccess Rate26.6—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniTrackHOTA23.45—Unverified
2DeepSORTHOTA21.16—Unverified
3OC-SORTHOTA20.83—Unverified
4ByteTrackHOTA20.66—Unverified
5TrackFormerHOTA19.62—Unverified
6HybridSORTHOTA16.64—Unverified
7DiffMOTHOTA16.4—Unverified
8Bot-SORTHOTA15.77—Unverified
#ModelMetricClaimedVerifiedStatus
1DiMP50Success Rate67.33—Unverified
2PrDiMP50Success Rate67—Unverified
3PrDiMP18Success Rate65.9—Unverified
4DiMP18Success Rate64.6—Unverified
5AtomSuccess Rate63.8—Unverified
#ModelMetricClaimedVerifiedStatus
1finalHumans0.14—Unverified
2night_furyHumans0.05—Unverified
3Yolo based methodHumans0.02—Unverified
4finalHumans0—Unverified
#ModelMetricClaimedVerifiedStatus
1M2-Trackmean precision83.4—Unverified
2BATmean precision75.2—Unverified
#ModelMetricClaimedVerifiedStatus
1UMMT3DMOTA95—Unverified
2MMPTRACK3DMOTA94.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Siam-FCAverage IOU0.66—Unverified
#ModelMetricClaimedVerifiedStatus
1RT-MDNetPrecision Plot0.63—Unverified