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 801–825 of 1966 papers

TitleStatusHype
Strong-TransCenter: Improved Multi-Object Tracking based on Transformers with Dense RepresentationsCode1
A Flexible-Frame-Rate Vision-Aided Inertial Object Tracking System for Mobile Devices—0
A Complete Recipe for Bayesian Knowledge Transfer: Object Tracking—0
Cell tracking for live-cell microscopy using an activity-prioritized assignment strategyCode0
Self-Supervised Learning via Maximum Entropy CodingCode1
RT-MOT: Confidence-Aware Real-Time Scheduling Framework for Multi-Object Tracking Tasks—0
RLM-Tracking: Online Multi-Pedestrian Tracking Supported by Relative Location Mapping—0
Track Targets by Dense Spatio-Temporal Position Encoding—0
Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices—0
AttTrack: Online Deep Attention Transfer for Multi-object Tracking—0
OST: Efficient One-stream Network for 3D Single Object Tracking in Point Clouds—0
Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?Code1
Instance Segmentation with Cross-Modal Consistency—0
QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object TrackingCode2
EnsembleMOT: A Step towards Ensemble Learning of Multiple Object TrackingCode1
TRADE: Object Tracking with 3D Trajectory and Ground Depth Estimates for UAVs—0
Trans2k: Unlocking the Power of Deep Models for Transparent Object TrackingCode1
GMA3D: Local-Global Attention Learning to Estimate Occluded Motions of Scene FlowCode0
Multiple Object Tracking from appearance by hierarchically clustering trackletsCode1
MOTSLAM: MOT-assisted monocular dynamic SLAM using single-view depth estimation—0
SoccerNet 2022 Challenges ResultsCode1
Movement Analytics: Current Status, Application to Manufacturing, and Future Prospects from an AI Perspective—0
Interpretable Deep Tracking—0
Exploiting More Information in Sparse Point Cloud for 3D Single Object TrackingCode0
Transformers for Object Detection in Large Point Clouds—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