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 1401–1425 of 1966 papers

TitleStatusHype
MOTS: Multiple Object Tracking for General Categories Based On Few-Shot Method—0
Taskology: Utilizing Task Relations at Scale—0
Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks—0
Computer Vision Toolkit for Non-invasive Monitoring of Factory Floor Artifacts—0
TSDM: Tracking by SiamRPN++ with a Depth-refiner and a Mask-generatorCode1
Derivation of a Constant Velocity Motion Model for Visual Tracking—0
DroTrack: High-speed Drone-based Object Tracking Under UncertaintyCode1
Joint Inference of States, Robot Knowledge, and Human (False-)Beliefs—0
Bayesian nonparametric modeling for predicting dynamic dependencies in multiple object tracking—0
How to track your dragon: A Multi-Attentional Framework for real-time RGB-D 6-DOF Object Pose TrackingCode0
Joint Spatial-Temporal Optimization for Stereo 3D Object Tracking—0
MOPT: Multi-Object Panoptic Tracking—0
Fast Template Matching and Update for Video Object Tracking and SegmentationCode1
ArTIST: Autoregressive Trajectory Inpainting and Scoring for Tracking—0
Multi-Object Tracking with Siamese Track-RCNN—0
SQE: a Self Quality Evaluation Metric for Parameters Optimization in Multi-Object Tracking—0
Deformable Siamese Attention Networks for Visual Object TrackingCode1
End-to-end Learning Improves Static Object Geo-localization in Monocular VideoCode1
Deep Multi-Shot Network for modelling Appearance Similarity in Multi-Person Tracking applications—0
FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object TrackingCode1
Effective Fusion of Deep Multitasking Representations for Robust Visual Tracking—0
RetinaTrack: Online Single Stage Joint Detection and TrackingCode1
Supervised and Unsupervised Detections for Multiple Object Tracking in Traffic Scenes: A Comparative StudyCode0
Probabilistic Regression for Visual Tracking—0
Online and Real-time Object Tracking Algorithm with Extremely Small Matrices—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