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

Showing 15011550 of 1966 papers

TitleStatusHype
Tracking system of Mine Patrol Robot for Low Illumination Environment0
Tracking System to Automate Data Collection of Microscopic Pedestrian Traffic Flow0
Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking0
Tracking the Untrackable0
Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution0
Tracking Virtual Meetings in the Wild: Re-identification in Multi-Participant Virtual Meetings0
Tracking with multi-level features0
Tracking without Label: Unsupervised Multiple Object Tracking via Contrastive Similarity Learning0
Tracking Without Re-recognition in Humans and Machines0
Tracklet Association Tracker: An End-to-End Learning-based Association Approach for Multi-Object Tracking0
TrackMPNN: A Message Passing Graph Neural Architecture for Multi-Object Tracking0
TrackNet: Simultaneous Object Detection and Tracking and Its Application in Traffic Video Analysis0
TrackNetV4: Enhancing Fast Sports Object Tracking with Motion Attention Maps0
Track Targets by Dense Spatio-Temporal Position Encoding0
Track, then Decide: Category-Agnostic Vision-based Multi-Object Tracking0
TRADE: Object Tracking with 3D Trajectory and Ground Depth Estimates for UAVs0
TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios0
Trajectory Factory: Tracklet Cleaving and Re-connection by Deep Siamese Bi-GRU for Multiple Object Tracking0
Trajectory Poisson multi-Bernoulli mixture filter for traffic monitoring using a drone0
Transferring Rich Feature Hierarchies for Robust Visual Tracking0
TransFiner: A Full-Scale Refinement Approach for Multiple Object Tracking0
TransFlow: Transformer as Flow Learner0
Transformer-Based Multi-Object Smoothing with Decoupled Data Association and Smoothing0
Transformer Network for Multi-Person Tracking and Re-Identification in Unconstrained Environment0
Transformers for Multi-Object Tracking on Point Clouds0
Transformers for Object Detection in Large Point Clouds0
Transformers in Single Object Tracking: An Experimental Survey0
Transformers Meet Visual Learning Understanding: A Comprehensive Review0
Transparent Object Tracking Benchmark0
Trashbusters: Deep Learning Approach for Litter Detection and Tracking0
TRAT: Tracking by Attention Using Spatio-Temporal Features0
Triplet Loss in Siamese Network for Object Tracking0
TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTM0
TR-MOT: Multi-Object Tracking by Reference0
TwistSLAM: Constrained SLAM in Dynamic Environment0
TwistSLAM++: Fusing multiple modalities for accurate dynamic semantic SLAM0
Two stages for visual object tracking0
Type-to-Track: Retrieve Any Object via Prompt-based Tracking0
UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking0
S2-Track: A Simple yet Strong Approach for End-to-End 3D Multi-Object Tracking0
UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles0
UHP-SOT: An Unsupervised High-Performance Single Object Tracker0
Uncertainty Aware Active Learning for Reconfiguration of Pre-trained Deep Object-Detection Networks for New Target Domains0
Uncertainty in Minimum Cost Multicuts for Image and Motion Segmentation0
Understanding Long Videos via LLM-Powered Entity Relation Graphs0
Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation0
Unified Graph based Multi-Cue Feature Fusion for Robust Visual Tracking0
UniHPE: Towards Unified Human Pose Estimation via Contrastive Learning0
UniQuadric: A SLAM Backend for Unknown Rigid Object 3D Tracking and Light-Weight Modeling0
Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HR-CEUTrack-LargeSuccess Rate65Unverified
2HR-CEUTrack-BaseSuccess Rate63.2Unverified
3CEUTrack-LargeSuccess Rate62.8Unverified
4CEUTrack-BaseSuccess Rate62Unverified
5SiamR-CNNSuccess Rate60.9Unverified
6TransTSuccess Rate60.5Unverified
7SuperDiMPSuccess Rate60.2Unverified
8TrDiMPSuccess Rate60.1Unverified
9KeepTrackSuccess Rate59.6Unverified
10AiATrackSuccess Rate59Unverified
#ModelMetricClaimedVerifiedStatus
1HR-MonTrack-BaseSuccess Rate68.5Unverified
2HR-MonTrack-TinySuccess Rate66.3Unverified
3Multi-modalSuccess Rate63.4Unverified
4PrDiMPSuccess Rate59Unverified
5DiMPSuccess Rate57.1Unverified
6MonTrackSuccess Rate54.9Unverified
7ATOMSuccess Rate46.5Unverified
8KYSSuccess Rate26.6Unverified
#ModelMetricClaimedVerifiedStatus
1OmniTrackHOTA23.45Unverified
2DeepSORTHOTA21.16Unverified
3OC-SORTHOTA20.83Unverified
4ByteTrackHOTA20.66Unverified
5TrackFormerHOTA19.62Unverified
6HybridSORTHOTA16.64Unverified
7DiffMOTHOTA16.4Unverified
8Bot-SORTHOTA15.77Unverified
#ModelMetricClaimedVerifiedStatus
1DiMP50Success Rate67.33Unverified
2PrDiMP50Success Rate67Unverified
3PrDiMP18Success Rate65.9Unverified
4DiMP18Success Rate64.6Unverified
5AtomSuccess Rate63.8Unverified
#ModelMetricClaimedVerifiedStatus
1finalHumans0.14Unverified
2night_furyHumans0.05Unverified
3Yolo based methodHumans0.02Unverified
4finalHumans0Unverified
#ModelMetricClaimedVerifiedStatus
1M2-Trackmean precision83.4Unverified
2BATmean precision75.2Unverified
#ModelMetricClaimedVerifiedStatus
1UMMT3DMOTA95Unverified
2MMPTRACK3DMOTA94.8Unverified
#ModelMetricClaimedVerifiedStatus
1Siam-FCAverage IOU0.66Unverified
#ModelMetricClaimedVerifiedStatus
1RT-MDNetPrecision Plot0.63Unverified