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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1301–1325 of 1966 papers

TitleStatusHype
Antithetic and Monte Carlo kernel estimators for partial rankings—0
An Uncertainty-Aware Performance Measure for Multi-Object Tracking—0
Applying r-spatiogram in object tracking for occlusion handling—0
Argus: Efficient Activity Detection System for Extended Video Analysis—0
A Robust Deep Networks based Multi-Object MultiCamera Tracking System for City Scale Traffic—0
A Robust Local Binary Similarity Pattern for Foreground Object Detection—0
ArTIST: Autoregressive Trajectory Inpainting and Scoring for Tracking—0
A Semi-automatic System for Ground Truth Generation of Soccer Video Sequences—0
A Simple Baseline for Pose Tracking in Videos of Crowded Scenes—0
A Strong Feature Representation for Siamese Network Tracker—0
A Survey for Deep RGBT Tracking—0
A Survey on Hardware Implementations of Visual Object Trackers—0
Asynchronous Tracking-by-Detection on Adaptive Time Surfaces for Event-based Object Tracking—0
Attention-Aware Multi-View Pedestrian Tracking—0
AttMOT: Improving Multiple-Object Tracking by Introducing Auxiliary Pedestrian Attributes—0
AttTrack: Online Deep Attention Transfer for Multi-object Tracking—0
A two-stage data association approach for 3D Multi-object Tracking—0
Audio Surveillance: a Systematic Review—0
A unified approach for multi-object triangulation, tracking and camera calibration—0
Unifying Tracking and Image-Video Object Detection—0
A Unified Multi-view Multi-person Tracking Framework—0
A unified neural network for object detection, multiple object tracking and vehicle re-identification—0
Automated Analysis of Femoral Artery Calcification Using Machine Learning Techniques—0
Automated Ground Truth Estimation of Vulnerable Road Users in Automotive Radar Data Using GNSS—0
Automated learning with a probabilistic programming language: Birch—0
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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