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 851–900 of 1966 papers

TitleStatusHype
Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications—0
Deep Reinforcement Learning with Iterative Shift for Visual Tracking—0
Joint Inference of States, Robot Knowledge, and Human (False-)Beliefs—0
AttMOT: Improving Multiple-Object Tracking by Introducing Auxiliary Pedestrian Attributes—0
Joint Learning of Siamese CNNs and Temporally Constrained Metrics for Tracklet Association—0
Deep Siamese Networks with Bayesian non-Parametrics for Video Object Tracking—0
A fast multi-object tracking system using an object detector ensemble—0
Correlation Filters with Limited Boundaries—0
Local Subspace Collaborative Tracking—0
Marrying Tracking with ELM: A Metric Constraint Guided Multiple Feature Fusion Method—0
Joint Spatial-Temporal Calibration for Camera and Global Pose Sensor—0
Joint Spatial-Temporal Optimization for Stereo 3D Object Tracking—0
Globally Optimal Object Tracking with Fully Convolutional Networks—0
Global Correlation Network: End-to-End Joint Multi-Object Detection and Tracking—0
GLAN: A Graph-based Linear Assignment Network—0
A Large Scale Urban Surveillance Video Dataset for Multiple-Object Tracking and Behavior Analysis—0
CorrBEV: Multi-View 3D Object Detection by Correlation Learning with Multi-modal Prototypes—0
Keypoint-based object tracking and localization using networks of low-power embedded smart cameras—0
Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood Maps—0
GeoWATCH for Detecting Heavy Construction in Heterogeneous Time Series of Satellite Images—0
Coreset-Based Adaptive Tracking—0
Label and Sample: Efficient Training of Vehicle Object Detector from Sparsely Labeled Data—0
Label Space Partition Selection for Multi-Object Tracking Using Two-Layer Partitioning—0
Generating Synthetic Training Data for Deep Learning-Based UAV Trajectory Prediction—0
Generating superpixels using deep image representations—0
Attention-Aware Multi-View Pedestrian Tracking—0
Large Margin Object Tracking with Circulant Feature Maps—0
Large Margin Structured Convolution Operator for Thermal Infrared Object Tracking—0
LMGP: Lifted Multicut Meets Geometry Projections for Multi-Camera Multi-Object Tracking—0
Aerial multi-object tracking by detection using deep association networks—0
Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation—0
A Proposed Artificial intelligence Model for Real-Time Human Action Localization and Tracking—0
Generalized Bayesian Filtering via Sequential Monte Carlo—0
Latent Constrained Correlation Filter—0
LDTrack: Dynamic People Tracking by Service Robots using Diffusion Models—0
Generalised Bayesian Filtering via Sequential Monte Carlo—0
Convolutional Unscented Kalman Filter for Multi-Object Tracking with Outliers—0
Linear Object Detection in Document Images using Multiple Object Tracking—0
General Compression Framework for Efficient Transformer Object Tracking—0
Depth Masked Discriminative Correlation Filter—0
Learning a Fast 3D Spectral Approach to Object Segmentation and Tracking over Space and Time—0
Learning a Neural Association Network for Self-supervised Multi-Object Tracking—0
Convolutional Regression for Visual Tracking—0
Convolutional Recurrent Predictor: Implicit Representation for Multi-target Filtering and Tracking—0
Limitation of Acyclic Oriented Graphs Matching as Cell Tracking Accuracy Measure when Evaluating Mitosis—0
GAKP: GRU Association and Kalman Prediction for Multiple Object Tracking—0
Gaga: Group Any Gaussians via 3D-aware Memory Bank—0
Convolutional Neural Networks in Orthodontics: a review—0
Derivation of a Constant Velocity Motion Model for Visual Tracking—0
FusionTrack: End-to-End Multi-Object Tracking in Arbitrary Multi-View Environment—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