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 601–650 of 1966 papers

TitleStatusHype
Heterogeneous Diversity Driven Active Learning for Multi-Object Tracking—0
BCOT: A Markerless High-Precision 3D Object Tracking Benchmark—0
Dense Scene Multiple Object Tracking with Box-Plane Matching—0
Bayesian Smoothing for the Extended Object Random Matrix Model—0
Dense Optical Flow Estimation Using Sparse Regularizers from Reduced Measurements—0
DeNoising-MOT: Towards Multiple Object Tracking with Severe Occlusions—0
A comparison of extended object tracking with multi-modal sensors in indoor environment—0
Bayesian Nonparametrics: An Alternative to Deep Learning—0
Bayesian nonparametric modeling for predicting dynamic dependencies in multiple object tracking—0
A Large Scale Urban Surveillance Video Dataset for Multiple-Object Tracking and Behavior Analysis—0
Head Mounted Pupil Tracking Using Convolutional Neural Network—0
Deformable Object Tracking with Gated Fusion—0
Basketball-SORT: An Association Method for Complex Multi-object Occlusion Problems in Basketball Multi-object Tracking—0
BASE: Probably a Better Approach to Multi-Object Tracking—0
Deep Siamese Networks with Bayesian non-Parametrics for Video Object Tracking—0
A Joint Intensity-Neuromorphic Event Imaging System for Resource Constrained Devices—0
A Comparison of CNN and Classic Features for Image Retrieval—0
DeepScale: Online Frame Size Adaptation for Multi-object Tracking on Smart Cameras and Edge Servers—0
Deep Reinforcement Learning with Iterative Shift for Visual Tracking—0
BankTweak: Adversarial Attack against Multi-Object Trackers by Manipulating Feature Banks—0
Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey—0
Deep Reinforcement Learning for Visual Object Tracking in Videos—0
Balancing Shared and Task-Specific Representations: A Hybrid Approach to Depth-Aware Video Panoptic Segmentation—0
AirTrack: Onboard Deep Learning Framework for Long-Range Aircraft Detection and Tracking—0
Hard Occlusions in Visual Object Tracking—0
Bags of Affine Subspaces for Robust Object Tracking—0
Deep Neural Networks—0
Deep Network Flow for Multi-Object Tracking—0
A CNN-LSTM Architecture for Marine Vessel Track Association Using Automatic Identification System (AIS) Data—0
Deep Multi-Shot Network for modelling Appearance Similarity in Multi-Person Tracking applications—0
BackTrack: Robust template update via Backward Tracking of candidate template—0
Handling Heavy Occlusion in Dense Crowd Tracking by Focusing on the Heads—0
DeepMix: Online Auto Data Augmentation for Robust Visual Object Tracking—0
Background Subtraction with Real-time Semantic Segmentation—0
Haptic Repurposing with GenAI—0
Heteroskedastic Geospatial Tracking with Distributed Camera Networks—0
Deep-LK for Efficient Adaptive Object Tracking—0
Deep LG-Track: An Enhanced Localization-Confidence-Guided Multi-Object Tracker—0
Deep Learning Techniques for Video Instance Segmentation: A Survey—0
Deep Learning of Appearance Models for Online Object Tracking—0
Background subtraction on depth videos with convolutional neural networks—0
Deep Learning Method for Cell-Wise Object Tracking, Velocity Estimation and Projection of Sensor Data over Time—0
Deep Learning in Video Multi-Object Tracking: A Survey—0
BaboonLand Dataset: Tracking Primates in the Wild and Automating Behaviour Recognition from Drone Videos—0
Deep Learning for UAV-based Object Detection and Tracking: A Survey—0
Deep Learning-Based Robust Multi-Object Tracking via Fusion of mmWave Radar and Camera Sensors—0
A Wide-area, Low-latency, and Power-efficient 6-DoF Pose Tracking System for Rigid Objects—0
A Hypergradient Approach to Robust Regression without Correspondence—0
A Certifiable Security Patch for Object Tracking in Self-Driving Systems via Historical Deviation Modeling—0
Deep Learning-Based Multi-Object Tracking: A Comprehensive Survey from Foundations to State-of-the-Art—0
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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