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 526–550 of 1966 papers

TitleStatusHype
CGTrack: Cascade Gating Network with Hierarchical Feature Aggregation for UAV TrackingCode0
SMMT: Siamese Motion Mamba with Self-attention for Thermal Infrared Target Tracking—0
Interactive Instance Annotation with Siamese Networks—0
Optimizing Indoor Farm Monitoring Efficiency Using UAV: Yield Estimation in a GNSS-Denied Cherry Tomato Greenhouse—0
A Robust Deep Networks based Multi-Object MultiCamera Tracking System for City Scale Traffic—0
MoSAM: Motion-Guided Segment Anything Model with Spatial-Temporal Memory Selection—0
Stereo X-ray tomography on deformed object tracking—0
Enhancing Self-Supervised Fine-Grained Video Object Tracking with Dynamic Memory Prediction—0
The Mean of Multi-Object Trajectories—0
Improving trajectory continuity in drone-based crowd monitoring using a set of minimal-cost techniques and deep discriminative correlation filters—0
Multi-Sensor Fusion of Active and Passive Measurements for Extended Object Tracking—0
Adversarial Attack for RGB-Event based Visual Object TrackingCode0
Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving—0
Robust Visual Servoing under Human Supervision for Assembly Tasks—0
WildLive: Near Real-time Visual Wildlife Tracking onboard UAVs—0
Intelligent driving vehicle front multi-target tracking and detection based on YOLOv5 and point cloud 3D projection—0
Multi-Object Tracking for Collision Avoidance Using Multiple Cameras in Open RAN Networks—0
Risk-Aware Robot Control in Dynamic Environments Using Belief Control Barrier FunctionsCode0
TQD-Track: Temporal Query Denoising for 3D Multi-Object Tracking—0
Data-Driven Object Tracking: Integrating Modular Neural Networks into a Kalman Framework—0
Attention-Aware Multi-View Pedestrian Tracking—0
Deep LG-Track: An Enhanced Localization-Confidence-Guided Multi-Object Tracker—0
COST: Contrastive One-Stage Transformer for Vision-Language Small Object Tracking—0
Towards Mobile Sensing with Event Cameras on High-agility Resource-constrained Devices: A Survey—0
Hyperspectral Adapter for Object Tracking based on Hyperspectral Video—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