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 1901–1950 of 1966 papers

TitleStatusHype
Multi-object Tracking with a Hierarchical Single-branch Network—0
Multi-Object Tracking with Camera-LiDAR Fusion for Autonomous Driving—0
Multi-Object Tracking with Deep Learning Ensemble for Unmanned Aerial System Applications—0
Multi-Object Tracking with Hallucinated and Unlabeled Videos—0
Multi-Object Tracking with Multiple Cues and Switcher-Aware Classification—0
Multi-object Tracking with Neural Gating Using Bilinear LSTM—0
Multi-Object Tracking With Quadruplet Convolutional Neural Networks—0
Multi-object tracking with self-supervised associating network—0
Multi-Object Tracking with Siamese Track-RCNN—0
Multi-person Articulated Tracking with Spatial and Temporal Embeddings—0
Multi Player Tracking in Ice Hockey with Homographic Projections—0
Multiple Feature Fusion via Weighted Entropy for Visual Tracking—0
Multiple objects tracking in surveillance video using color and Hu moments—0
Multiple Object Tracking: A Literature Review—0
Multiple Object Tracking based on Occlusion-Aware Embedding Consistency Learning—0
Multiple Object Tracking by Flowing and Fusing—0
Multiple-object tracking in cluttered and crowded public spaces—0
Multiple Object Tracking in Recent Times: A Literature Review—0
Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detector—0
Multiple object tracking with context awareness—0
Multiple Object Tracking with Correlation Learning—0
Multiple Object Tracking with Mixture Density Networks for Trajectory Estimation—0
Multiple Object Tracking with Motion and Appearance Cues—0
Multiple Pedestrians and Vehicles Tracking in Aerial Imagery: A Comprehensive Study—0
Multiple Planar Object Tracking—0
Multiple Trajectory Prediction with Deep Temporal and Spatial Convolutional Neural Networks—0
Multiple-Vehicle Tracking in the Highway Using Appearance Model and Visual Object Tracking—0
Multiresolution analysis on the symmetric group—0
Multi-Scene Generalized Trajectory Global Graph Solver with Composite Nodes for Multiple Object Tracking—0
Multi-Sensor Fusion of Active and Passive Measurements for Extended Object Tracking—0
Multi-Ship Tracking by Robust Similarity metric—0
MUlti-Store Tracker (MUSTer): A Cognitive Psychology Inspired Approach to Object Tracking—0
Multi-Target Active Object Tracking with Monte Carlo Tree Search and Target Motion Modeling—0
Multi-Task Correlation Particle Filter for Robust Object Tracking—0
Multi-Task Reinforcement Learning based Mobile Manipulation Control for Dynamic Object Tracking and Grasping—0
Improving Siamese Based Trackers with Light or No Training through Multiple Templates and Temporal Network—0
Multi-View People Tracking via Hierarchical Trajectory Composition—0
MVA 2025 Small Multi-Object Tracking for Spotting Birds Challenge: Dataset, Methods, and Results—0
MV-YOLO: Motion Vector-aided Tracking by Semantic Object Detection—0
Network Comparison Study of Deep Activation Feature Discriminability with Novel Objects—0
Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactions—0
NeuralHOFusion: Neural Volumetric Rendering under Human-object Interactions—0
Neural Memory Plasticity for Anomaly Detection—0
Neural Network Kalman filtering for 3D object tracking from linear array ultrasound data—0
Neuromorphic Optical Tracking and Imaging of Randomly Moving Targets through Strongly Scattering Media—0
New Performance Measures for Object Tracking under Complex Environments—0
Non-Markovian Globally Consistent Multi-Object Tracking—0
Non-planar Object Detection and Identification by Features Matching and Triangulation Growth—0
Non-rigid Object Tracking via Deep Multi-scale Spatial-temporal Discriminative Saliency Maps—0
Non-Rigid Object Tracking via Deformable Patches Using Shape-Preserved KCF and Level Sets—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