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 17511800 of 1966 papers

TitleStatusHype
Keypoint-based object tracking and localization using networks of low-power embedded smart cameras0
Heuristic Search for Structural Constraints in Data Association0
A Survey on Hardware Implementations of Visual Object Trackers0
Recurrent Autoregressive Networks for Online Multi-Object Tracking0
DART: Distribution Aware Retinal Transform for Event-based Cameras0
Deep Neural Networks0
Deep Convolutional Neural Networks for Thermal Infrared Object TrackingCode1
Visual Tracking via Dynamic Graph Learning0
Robust Object Tracking Based on Temporal and Spatial Deep Networks0
Non-Rigid Object Tracking via Deformable Patches Using Shape-Preserved KCF and Level Sets0
Non-Markovian Globally Consistent Multi-Object Tracking0
Long Short-Term Memory Kalman Filters: Recurrent Neural Estimators for Pose Regularization0
Learning Dynamic Siamese Network for Visual Object Tracking0
Multi-camera Multi-Object Tracking0
Rotation Adaptive Visual Object Tracking with Motion ConsistencyCode0
ClickBAIT: Click-based Accelerated Incremental Training of Convolutional Neural Networks0
Real-Time Multiple Object Tracking - A Study on the Importance of SpeedCode0
CoBe -- Coded Beacons for Localization, Object Tracking, and SLAM AugmentationCode0
Efficiently Tracking Homogeneous Regions in Multichannel Images0
Convolutional Neural Networks for Non-iterative Reconstruction of Compressively Sensed Images0
Online Multi-Object Tracking Using CNN-based Single Object Tracker with Spatial-Temporal Attention Mechanism0
Learning Policies for Adaptive Tracking with Deep Feature Cascades0
Long Short-Term Memory Kalman Filters:Recurrent Neural Estimators for Pose Regularization0
Better Together: Joint Reasoning for Non-rigid 3D Reconstruction with Specularities and Shading0
Patch-based adaptive weighting with segmentation and scale (PAWSS) for visual tracking0
Kernalised Multi-resolution Convnet for Visual TrackingCode0
Infinite Latent Feature Selection: A Probabilistic Latent Graph-Based Ranking Approach0
Video Object Segmentation using Tracked Object Proposals0
Spectral Filter Tracking0
Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood Maps0
Adaptive Correlation Filters with Long-Term and Short-Term Memory for Object TrackingCode0
An Efficient Background Term for 3D Reconstruction and Tracking With Smooth Surface Models0
Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications0
Multi-Task Correlation Particle Filter for Robust Object Tracking0
Multi-Object Tracking With Quadruplet Convolutional Neural Networks0
Hierarchical Attentive Recurrent TrackingCode0
Deep Network Flow for Multi-Object Tracking0
End-to-end Active Object Tracking via Reinforcement Learning0
Learning a Robust Society of Tracking Parts0
Object Tracking based on Quantum Particle Swarm Optimization0
Fusion of Head and Full-Body Detectors for Multi-Object Tracking0
Dynamics Based 3D Skeletal Hand TrackingCode0
Deep-LK for Efficient Adaptive Object Tracking0
Quadruplet Network with One-Shot Learning for Fast Visual Object Tracking0
Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic ObjectsCode0
(Quasi)Periodicity Quantification in Video Data, Using TopologyCode0
Measuring the Accuracy of Object Detectors and Trackers0
Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition0
A data set for evaluating the performance of multi-class multi-object video tracking0
Identifying First-person Camera Wearers in Third-person Videos0
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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