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 1601–1650 of 1966 papers

TitleStatusHype
Extending Multi-Object Tracking systems to better exploit appearance and 3D information—0
Extension of Sinkhorn Method: Optimal Movement Estimation of Agents Moving at Constant Velocity—0
Extensions of the Sign Language Recognition and Translation Corpus RWTH-PHOENIX-Weather—0
Eye in the Sky: Drone-Based Object Tracking and 3D Localization—0
FACT: Feature Adaptive Continual-learning Tracker for Multiple Object Tracking—0
Factor Graph based 3D Multi-Object Tracking in Point Clouds—0
FAMNet: Joint Learning of Feature, Affinity and Multi-dimensional Assignment for Online Multiple Object Tracking—0
Fast CNN-Based Object Tracking Using Localization Layers and Deep Features Interpolation—0
Faster and Simpler Siamese Network for Single Object Tracking—0
Faster object tracking pipeline for real time tracking—0
Fast Integral Image Estimation at 1% measurement rate—0
Fast keypoint detection in video sequences—0
Fast Point Cloud to Mesh Reconstruction for Deformable Object Tracking—0
Fast Single Shot Detection and Pose Estimation—0
FastTrackTr:Towards Fast Multi-Object Tracking with Transformers—0
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching—0
FeatureSORT: Essential Features for Effective Tracking—0
Few-Shot Keypoint Detection as Task Adaptation via Latent Embeddings—0
F&F Attack: Adversarial Attack against Multiple Object Trackers by Inducing False Negatives and False Positives—0
Tracklets Predicting Based Adaptive Graph Tracking—0
First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks—0
Flow Guided Short-term Trackers with Cascade Detection for Long-term Tracking—0
FlowMOT: 3D Multi-Object Tracking by Scene Flow Association—0
FlowTrack: Point-level Flow Network for 3D Single Object Tracking—0
Focus On Details: Online Multi-object Tracking with Diverse Fine-grained Representation—0
FOLT: Fast Multiple Object Tracking from UAV-captured Videos Based on Optical Flow—0
FOMTrace: Interactive Video Segmentation By Image Graphs and Fuzzy Object Models—0
Foreground-Background Distribution Modeling Transformer for Visual Object Tracking—0
Forensic Video Analytic Software—0
FPAN: Fine-grained and Progressive Attention Localization Network for Data Retrieval—0
Frame-wise Motion and Appearance for Real-time Multiple Object Tracking—0
From Two-Stream to One-Stream: Efficient RGB-T Tracking via Mutual Prompt Learning and Knowledge Distillation—0
F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking—0
Full-Angle Quaternions for Robustly Matching Vectors of 3D Rotations—0
Full Reference Objective Quality Assessment for Reconstructed Background Images—0
Fully Spiking Neural Networks for Unified Frame-Event Object Tracking—0
Fusion of Head and Full-Body Detectors for Multi-Object Tracking—0
FusionTrack: End-to-End Multi-Object Tracking in Arbitrary Multi-View Environment—0
Gaga: Group Any Gaussians via 3D-aware Memory Bank—0
GAKP: GRU Association and Kalman Prediction for Multiple Object Tracking—0
General Compression Framework for Efficient Transformer Object Tracking—0
Generalised Bayesian Filtering via Sequential Monte Carlo—0
Generalized Bayesian Filtering via Sequential Monte Carlo—0
Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation—0
Generating superpixels using deep image representations—0
Generating Synthetic Training Data for Deep Learning-Based UAV Trajectory Prediction—0
GeoWATCH for Detecting Heavy Construction in Heterogeneous Time Series of Satellite Images—0
GLAN: A Graph-based Linear Assignment Network—0
Global Correlation Network: End-to-End Joint Multi-Object Detection and Tracking—0
Globally Optimal Object Tracking with Fully Convolutional Networks—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