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 1101–1150 of 1966 papers

TitleStatusHype
Tracking without Label: Unsupervised Multiple Object Tracking via Contrastive Similarity Learning—0
Tracking Without Re-recognition in Humans and Machines—0
Tracklet Association Tracker: An End-to-End Learning-based Association Approach for Multi-Object Tracking—0
TrackMPNN: A Message Passing Graph Neural Architecture for Multi-Object Tracking—0
TrackNet: Simultaneous Object Detection and Tracking and Its Application in Traffic Video Analysis—0
TrackNetV4: Enhancing Fast Sports Object Tracking with Motion Attention Maps—0
Track Targets by Dense Spatio-Temporal Position Encoding—0
Track, then Decide: Category-Agnostic Vision-based Multi-Object Tracking—0
TRADE: Object Tracking with 3D Trajectory and Ground Depth Estimates for UAVs—0
TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios—0
Trajectory Factory: Tracklet Cleaving and Re-connection by Deep Siamese Bi-GRU for Multiple Object Tracking—0
Trajectory Poisson multi-Bernoulli mixture filter for traffic monitoring using a drone—0
Transferring Rich Feature Hierarchies for Robust Visual Tracking—0
TransFiner: A Full-Scale Refinement Approach for Multiple Object Tracking—0
TransFlow: Transformer as Flow Learner—0
Transformer-Based Multi-Object Smoothing with Decoupled Data Association and Smoothing—0
Transformer Network for Multi-Person Tracking and Re-Identification in Unconstrained Environment—0
Transformers for Multi-Object Tracking on Point Clouds—0
Transformers for Object Detection in Large Point Clouds—0
Transformers in Single Object Tracking: An Experimental Survey—0
Transformers Meet Visual Learning Understanding: A Comprehensive Review—0
Transparent Object Tracking Benchmark—0
Trashbusters: Deep Learning Approach for Litter Detection and Tracking—0
TRAT: Tracking by Attention Using Spatio-Temporal Features—0
Triplet Loss in Siamese Network for Object Tracking—0
TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTM—0
TR-MOT: Multi-Object Tracking by Reference—0
TwistSLAM: Constrained SLAM in Dynamic Environment—0
TwistSLAM++: Fusing multiple modalities for accurate dynamic semantic SLAM—0
Two stages for visual object tracking—0
Type-to-Track: Retrieve Any Object via Prompt-based Tracking—0
UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking—0
S2-Track: A Simple yet Strong Approach for End-to-End 3D Multi-Object Tracking—0
UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles—0
UHP-SOT: An Unsupervised High-Performance Single Object Tracker—0
Uncertainty Aware Active Learning for Reconfiguration of Pre-trained Deep Object-Detection Networks for New Target Domains—0
Uncertainty in Minimum Cost Multicuts for Image and Motion Segmentation—0
Understanding Long Videos via LLM-Powered Entity Relation Graphs—0
Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation—0
Unified Graph based Multi-Cue Feature Fusion for Robust Visual Tracking—0
UniHPE: Towards Unified Human Pose Estimation via Contrastive Learning—0
UniQuadric: A SLAM Backend for Unknown Rigid Object 3D Tracking and Light-Weight Modeling—0
Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis—0
UnsMOT: Unified Framework for Unsupervised Multi-Object Tracking with Geometric Topology Guidance—0
Unsupervised Green Object Tracker (GOT) without Offline Pre-training—0
Unsupervised learning-based long-term superpixel tracking—0
Unsupervised Learning of Object Structure and Dynamics from Videos—0
Unsupervised Lightweight Single Object Tracking with UHP-SOT++—0
Unsupervised Multiple-Object Tracking with a Dynamical Variational Autoencoder—0
Unsupervised Multiple Person Tracking using AutoEncoder-Based Lifted Multicuts—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