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 1751–1800 of 1966 papers

TitleStatusHype
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
Large Margin Object Tracking with Circulant Feature Maps—0
Large Margin Structured Convolution Operator for Thermal Infrared Object Tracking—0
Latent Constrained Correlation Filter—0
LDTrack: Dynamic People Tracking by Service Robots using Diffusion Models—0
Learnable Online Graph Representations for 3D Multi-Object Tracking—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
Learning a Robust Society of Tracking Parts using Co-occurrence Constraints—0
Learning a Robust Society of Tracking Parts—0
Learning Consistency Pursued Correlation Filters for Real-Time UAV Tracking—0
Learning Correspondence for Deformable Objects—0
Learning data association without data association: An EM approach to neural assignment prediction—0
Learning Dual-Fused Modality-Aware Representations for RGBD Tracking—0
Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking—0
Learning Dynamic Siamese Network for Visual Object Tracking—0
Learning feed-forward one-shot learners—0
Learning Global Structure Consistency for Robust Object Tracking—0
Learning Hierarchical Features for Visual Object Tracking with Recursive Neural Networks—0
Learning Irreducible Representations of Noncommutative Lie Groups—0
Learning Local Feature Descriptors for Multiple Object Tracking—0
Learning Mobile CNN Feature Extraction Toward Fast Computation of Visual Object Tracking—0
Learning Moving-Object Tracking with FMCW LiDAR—0
Learning Multi-Object Tracking and Segmentation from Automatic Annotations—0
Learning Non-Uniform Hypergraph for Multi-Object Tracking—0
Learning of Global Objective for Network Flow in Multi-Object Tracking—0
Learning Pixel Trajectories with Multiscale Contrastive Random Walks—0
Learning Policies for Adaptive Tracking with Deep Feature Cascades—0
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning—0
Learning Rotation Adaptive Correlation Filters in Robust Visual Object Tracking—0
Learning Spatial Distribution of Long-Term Trackers Scores—0
Learning Tactile Models for Factor Graph-based Estimation—0
Learning Target Candidate Association to Keep Track of What Not to Track—0
Learning Target-oriented Dual Attention for Robust RGB-T Tracking—0
Learning The Sequential Temporal Information with Recurrent Neural Networks—0
Learning to associate detections for real-time multiple object tracking—0
Learning to Track Any Object—0
Learning to Track: Online Multi-Object Tracking by Decision Making—0
Learning to Update for Object Tracking with Recurrent Meta-learner—0
Learning to Visually Connect Actions and their Effects—0
LEGO: Learning and Graph-Optimized Modular Tracker for Online Multi-Object Tracking with Point Clouds—0
Leveraging Temporal Cues for Semi-Supervised Multi-View 3D Object Detection—0
Leveraging the Power of Data Augmentation for Transformer-based Tracking—0
LiDAR MOT-DETR: A LiDAR-based Two-Stage Transformer for 3D Multiple Object Tracking—0
Lighter Stacked Hourglass Human Pose Estimation—0
Lightweight RGB-T Tracking with Mobile Vision Transformers—0
Limitation of Acyclic Oriented Graphs Matching as Cell Tracking Accuracy Measure when Evaluating Mitosis—0
Linear Object Detection in Document Images using Multiple Object Tracking—0
LMGP: Lifted Multicut Meets Geometry Projections for Multi-Camera Multi-Object Tracking—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