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 1226–1250 of 1966 papers

TitleStatusHype
4D Spatio-Temporal Convolutional Networks for Object Position Estimation in OCT Volumes—0
6DOPE-GS: Online 6D Object Pose Estimation using Gaussian Splatting—0
A2VIS: Amodal-Aware Approach to Video Instance Segmentation—0
AB3DMOT: A Baseline for 3D Multi-Object Tracking and New Evaluation Metrics—0
A Batch Update Using Multiplicative Noise Modelling for Extended Object Tracking—0
A Bayesian Filter for Multi-view 3D Multi-object Tracking with Occlusion Handling—0
A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning—0
ABCTracker: an easy-to-use, cloud-based application for tracking multiple objects—0
Accurate Anchor Free Tracking—0
Accurate Object Association and Pose Updating for Semantic SLAM—0
A Certifiable Security Patch for Object Tracking in Self-Driving Systems via Historical Deviation Modeling—0
A CNN-LSTM Architecture for Marine Vessel Track Association Using Automatic Identification System (AIS) Data—0
A Comparison of CNN and Classic Features for Image Retrieval—0
A comparison of extended object tracking with multi-modal sensors in indoor environment—0
A Complete Recipe for Bayesian Knowledge Transfer: Object Tracking—0
A Comprehensive Study of Object Tracking in Low-Light Environments—0
A Connectome Based Hexagonal Lattice Convolutional Network Model of the Drosophila Visual System—0
A Continuous, Full-scope, Spatio-temporal Tracking Metric based on KL-divergence—0
A CRF-based Framework for Tracklet Inactivation in Online Multi-Object Tracking—0
ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints—0
Active inference body perception and action for humanoid robots—0
Active Learning in Video Tracking—0
ACTrack: Adding Spatio-Temporal Condition for Visual Object Tracking—0
Adapting SAM 2 for Visual Object Tracking: 1st Place Solution for MMVPR Challenge Multi-Modal Tracking—0
Adaptive Objectness for Object Tracking—0
Show:102550
← PrevPage 50 of 79Next →
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