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 1351–1400 of 1966 papers

TitleStatusHype
Benchmarking Online Object Trackers for Underwater Robot Position Locking Applications—0
Benchmarking Robustness of AI-Enabled Multi-sensor Fusion Systems: Challenges and Opportunities—0
Benchmarking Vision-Based Object Tracking for USVs in Complex Maritime Environments—0
Better Together: Joint Reasoning for Non-rigid 3D Reconstruction with Specularities and Shading—0
MCBLT: Multi-Camera Multi-Object 3D Tracking in Long Videos—0
Beyond Boxes: Mask-Guided Spatio-Temporal Feature Aggregation for Video Object Detection—0
Beyond SOT: Tracking Multiple Generic Objects at Once—0
Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking—0
Beyond the Pixels: Exploring the Effects of Bit-Level Network and File Corruptions on Video Model Robustness—0
Beyond Traditional Single Object Tracking: A Survey—0
Beyond Visual Cues: Synchronously Exploring Target-Centric Semantics for Vision-Language Tracking—0
BihoT: A Large-Scale Dataset and Benchmark for Hyperspectral Camouflaged Object Tracking—0
Bi-label Propagation for Generic Multiple Object Tracking—0
Binary Quadratic Programing for Online Tracking of Hundreds of People in Extremely Crowded Scenes—0
BioDrone: A Bionic Drone-based Single Object Tracking Benchmark for Robust Vision—0
BlinkTrack: Feature Tracking over 100 FPS via Events and Images—0
Boosting Online 3D Multi-Object Tracking through Camera-Radar Cross Check—0
Bootstrapping Labelled Dataset Construction for Cow Tracking and Behavior Analysis—0
BOTT: Box Only Transformer Tracker for 3D Object Tracking—0
BronchoTrack: Airway Lumen Tracking for Branch-Level Bronchoscopic Localization—0
BuckTales : A multi-UAV dataset for multi-object tracking and re-identification of wild antelopes—0
Building a Mind Palace: Structuring Environment-Grounded Semantic Graphs for Effective Long Video Analysis with LLMs—0
CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking with Camera-LiDAR Fusion—0
CAMOT: Camera Angle-aware Multi-Object Tracking—0
CARPE-ID: Continuously Adaptable Re-identification for Personalized Robot Assistance—0
Category-Independent Articulated Object Tracking with Factor Graphs—0
CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark—0
CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark—0
Cell Multi-Bernoulli (Cell-MB) Sensor Control for Multi-object Search-While-Tracking (SWT)—0
CenterRadarNet: Joint 3D Object Detection and Tracking Framework using 4D FMCW Radar—0
CFTrack: Center-based Radar and Camera Fusion for 3D Multi-Object Tracking—0
ChatTracker: Enhancing Visual Tracking Performance via Chatting with Multimodal Large Language Model—0
Classification of Fused Images using Radial Basis Function Neural Network for Human Face Recognition—0
Classification of Polar-Thermal Eigenfaces using Multilayer Perceptron for Human Face Recognition—0
ClickBAIT: Click-based Accelerated Incremental Training of Convolutional Neural Networks—0
ClickBAIT-v2: Training an Object Detector in Real-Time—0
ClickTrack: Towards Real-time Interactive Single Object Tracking—0
Clustering of Static-Adaptive Correspondences for Deformable Object Tracking—0
CML-MOTS: Collaborative Multi-task Learning for Multi-Object Tracking and Segmentation—0
CoachAI: A Project for Microscopic Badminton Match Data Collection and Tactical Analysis—0
CoCoLoT: Combining Complementary Trackers in Long-Term Visual Tracking—0
Cognitive Disentanglement for Referring Multi-Object Tracking—0
Collaborative Deep Reinforcement Learning for Multi-Object Tracking—0
Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation—0
COLLIDE-PRED: Prediction of On-Road Collision From Surveillance Videos—0
Combining 3D Model Contour Energy and Keypoints for Object Tracking—0
Combining Background Subtraction Algorithms with Convolutional Neural Network—0
Evaluating and Improving Interactions with Hazy Oracles—0
COMET: Context-Aware IoU-Guided Network for Small Object Tracking—0
Common Corruptions for Enhancing and Evaluating Robustness in Air-to-Air Visual Object Detection—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