SOTAVerified

Multiple Object Tracking

Multiple Object Tracking is the problem of automatically identifying multiple objects in a video and representing them as a set of trajectories with high accuracy.

Source: SOT for MOT

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–175 of 318 papers

TitleStatusHype
Adaptive Confidence Threshold for ByteTrack in Multi-Object TrackingCode0
Multiple Toddler Tracking in Indoor VideosCode0
Contrastive Learning for Multi-Object Tracking with TransformersCode0
Multiple Object Tracking based on Occlusion-Aware Embedding Consistency Learning—0
DecoderTracker: Decoder-Only Method for Multiple-Object Tracking—0
COOLer: Class-Incremental Learning for Appearance-Based Multiple Object TrackingCode0
3D Multiple Object Tracking on Autonomous Driving: A Literature Review—0
Forensic Video Analytic Software—0
DeNoising-MOT: Towards Multiple Object Tracking with Severe Occlusions—0
LEGO: Learning and Graph-Optimized Modular Tracker for Online Multi-Object Tracking with Point Clouds—0
AttMOT: Improving Multiple-Object Tracking by Introducing Auxiliary Pedestrian Attributes—0
FOLT: Fast Multiple Object Tracking from UAV-captured Videos Based on Optical Flow—0
MotionTrack: End-to-End Transformer-based Multi-Object Tracing with LiDAR-Camera Fusion—0
UTOPIA: Unconstrained Tracking Objects without Preliminary Examination via Cross-Domain Adaptation—0
Tracking Objects with 3D Representation from Videos—0
MotionTrack: Learning Motion Predictor for Multiple Object Tracking—0
Z-GMOT: Zero-shot Generic Multiple Object Tracking—0
Linear Object Detection in Document Images using Multiple Object Tracking—0
Type-to-Track: Retrieve Any Object via Prompt-based Tracking—0
S^3Track: Self-supervised Tracking with Soft Assignment Flow—0
A Feasibility Study on Indoor Localization and Multi-person Tracking Using Sparsely Distributed Camera Network with Edge ComputingCode0
Handling Heavy Occlusion in Dense Crowd Tracking by Focusing on the Heads—0
Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation—0
Focus On Details: Online Multi-object Tracking with Diverse Fine-grained Representation—0
Spatio-Temporal Point Process for Multiple Object Tracking—0
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All datasetsKITTI Test (Online Methods)BDD100K valBDD100K testCroHDSportsMOTKITTI Test (Offline Methods)RADIATEWaymo Open DatasetGMOT-40UA-DETRACYouTube-Hands

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SRK ODESAMOTA90.03—Unverified
2MOSTFusionMOTA84.83—Unverified
3mmMOT-normalMOTA84.77—Unverified
43DTMOTA84.52—Unverified
5Mono3DTMOTA84.52—Unverified
6RRC-IIITHMOTA84.24—Unverified
7RobMOT (Dynamic)HOTA81.8—Unverified
8RobMOTHOTA81.76—Unverified
9MCTrackHOTA81.07—Unverified
10KFDLHOTA81.06—Unverified
#ModelMetricClaimedVerifiedStatus
1ByteTrackmMOTA45.5—Unverified
2UNINEXT-HmMOTA44.2—Unverified
3MOTRv2mMOTA43.6—Unverified
4QDTrackmMOTA42.1—Unverified
5ContrasTRmMOTA41.7—Unverified
6UnicornmMOTA41.2—Unverified
7TETermMOTA39.1—Unverified
8QDTrackmMOTA36.6—Unverified
9Adaptive-searching -windows TrackermMOTA34.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ContrasTRmMOTA42.8—Unverified
2SUSHImMOTA40.2—Unverified
3ByteTrackmMOTA40.1—Unverified
4QDtrackmMOTA35.6—Unverified
5Yu et al.mMOTA26.3—Unverified
#ModelMetricClaimedVerifiedStatus
1PP-TrackingMOTA72.6—Unverified
2OC-SORTMOTA67.9—Unverified
3HeadHunter-TMOTA63.6—Unverified
4TracktorMOTA58.9—Unverified
5SORTMOTA46.4—Unverified
#ModelMetricClaimedVerifiedStatus
1MOTIP (Deformable DETR, with SportsMOT val)HOTA75.2—Unverified
2TrackSSMHOTA74.4—Unverified
3MOTIP (Deformable DETR)HOTA71.9—Unverified
#ModelMetricClaimedVerifiedStatus
1MCTrackHOTA82.75—Unverified
2BiTrackHOTA82.7—Unverified
#ModelMetricClaimedVerifiedStatus
1SIRAMOTA47.79—Unverified
2TempoRadarMOTA37.91—Unverified
#ModelMetricClaimedVerifiedStatus
1QDTrackMOTA55.6—Unverified
2RetinaTrackMOTA44.92—Unverified
#ModelMetricClaimedVerifiedStatus
1MAC-SORTHOTA58.58—Unverified
#ModelMetricClaimedVerifiedStatus
1EB & TADNMOTA23.7—Unverified
#ModelMetricClaimedVerifiedStatus
1HandLerMOTA70—Unverified