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

Showing 14511500 of 1966 papers

TitleStatusHype
The 2nd Workshop on Maritime Computer Vision (MaCVi) 20240
The 3rd Anti-UAV Workshop & Challenge: Methods and Results0
The Challenge of Appearance-Free Object Tracking with Feedforward Neural Networks0
The detection and rectification for identity-switch based on unfalsified control0
The Interstate-24 3D Dataset: a new benchmark for 3D multi-camera vehicle tracking0
The Mean of Multi-Object Trajectories0
The ParallelEye Dataset: Constructing Large-Scale Artificial Scenes for Traffic Vision Research0
The Progression of Transformers from Language to Vision to MOT: A Literature Review on Multi-Object Tracking with Transformers0
The Right (Angled) Perspective: Improving the Understanding of Road Scenes Using Boosted Inverse Perspective Mapping0
The Shortlist Method for Fast Computation of the Earth Mover's Distance and Finding Optimal Solutions to Transportation Problems0
The Solution for Single Object Tracking Task of Perception Test Challenge 20240
The Solution for the ICCV 2023 Perception Test Challenge 2023 -- Task 6 -- Grounded videoQA0
The Solution Path Algorithm for Identity-Aware Multi-Object Tracking0
The SpaceNet Multi-Temporal Urban Development Challenge0
The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking0
Three-Dimensional Extended Object Tracking and Shape Learning Using Gaussian Processes0
Time3D: End-to-End Joint Monocular 3D Object Detection and Tracking for Autonomous Driving0
Towards Accurate State Estimation: Kalman Filter Incorporating Motion Dynamics for 3D Multi-Object Tracking0
Towards Category Unification of 3D Single Object Tracking on Point Clouds0
Towards Class-agnostic Tracking Using Feature Decorrelation in Point Clouds0
Towards Discriminative Representation: Multi-view Trajectory Contrastive Learning for Online Multi-object Tracking0
Towards Efficient Training with Negative Samples in Visual Tracking0
Towards Mobile Sensing with Event Cameras on High-agility Resource-constrained Devices: A Survey0
Object Re-Identification from Point Clouds0
Towards real-time and energy efficient Siamese tracking -- a hardware-software approach0
TQD-Track: Temporal Query Denoising for 3D Multi-Object Tracking0
TrackAgent: 6D Object Tracking via Reinforcement Learning0
Track Any Peppers: Weakly Supervised Sweet Pepper Tracking Using VLMs0
Track Boosting and Synthetic Data Aided Drone Detection0
Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition0
TrackFlow: Multi-Object Tracking with Normalizing Flows0
Tracking 6-DoF Object Motion from Events and Frames0
Tracking and Reconstructing Hand Object Interactions from Point Cloud Sequences in the Wild0
Tracking by 3D Model Estimation of Unknown Objects in Videos0
Tracking by Associating Clips0
Tracking-by-Counting: Using Network Flows on Crowd Density Maps for Tracking Multiple Targets0
Tracking Deformable Parts via Dynamic Conditional Random Fields0
Tracking Emerges by Looking Around Static Scenes, with Neural 3D Mapping0
Tracking from Patterns: Learning Corresponding Patterns in Point Clouds for 3D Object Tracking0
Tracking in Aerial Hyperspectral Videos using Deep Kernelized Correlation Filters0
Tracking in Urban Traffic Scenes from Background Subtraction and Object Detection0
Tracking Multiple Deformable Objects in Egocentric Videos0
Tracking Multiple Moving Objects Using Unscented Kalman Filtering Techniques0
Tracking Noisy Targets: A Review of Recent Object Tracking Approaches0
Tracking objects that change in appearance with phase synchrony0
Tracking Objects with 3D Representation from Videos0
Tracking Particles Ejected From Active Asteroid Bennu With Event-Based Vision0
Tracking Players in a Badminton Court by Two Cameras0
Tracking Road Users using Constraint Programming0
Tracking Small Birds by Detection Candidate Region Filtering and Detection History-aware Association0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HR-CEUTrack-LargeSuccess Rate65Unverified
2HR-CEUTrack-BaseSuccess Rate63.2Unverified
3CEUTrack-LargeSuccess Rate62.8Unverified
4CEUTrack-BaseSuccess Rate62Unverified
5SiamR-CNNSuccess Rate60.9Unverified
6TransTSuccess Rate60.5Unverified
7SuperDiMPSuccess Rate60.2Unverified
8TrDiMPSuccess Rate60.1Unverified
9KeepTrackSuccess Rate59.6Unverified
10AiATrackSuccess Rate59Unverified
#ModelMetricClaimedVerifiedStatus
1HR-MonTrack-BaseSuccess Rate68.5Unverified
2HR-MonTrack-TinySuccess Rate66.3Unverified
3Multi-modalSuccess Rate63.4Unverified
4PrDiMPSuccess Rate59Unverified
5DiMPSuccess Rate57.1Unverified
6MonTrackSuccess Rate54.9Unverified
7ATOMSuccess Rate46.5Unverified
8KYSSuccess Rate26.6Unverified
#ModelMetricClaimedVerifiedStatus
1OmniTrackHOTA23.45Unverified
2DeepSORTHOTA21.16Unverified
3OC-SORTHOTA20.83Unverified
4ByteTrackHOTA20.66Unverified
5TrackFormerHOTA19.62Unverified
6HybridSORTHOTA16.64Unverified
7DiffMOTHOTA16.4Unverified
8Bot-SORTHOTA15.77Unverified
#ModelMetricClaimedVerifiedStatus
1DiMP50Success Rate67.33Unverified
2PrDiMP50Success Rate67Unverified
3PrDiMP18Success Rate65.9Unverified
4DiMP18Success Rate64.6Unverified
5AtomSuccess Rate63.8Unverified
#ModelMetricClaimedVerifiedStatus
1finalHumans0.14Unverified
2night_furyHumans0.05Unverified
3Yolo based methodHumans0.02Unverified
4finalHumans0Unverified
#ModelMetricClaimedVerifiedStatus
1M2-Trackmean precision83.4Unverified
2BATmean precision75.2Unverified
#ModelMetricClaimedVerifiedStatus
1UMMT3DMOTA95Unverified
2MMPTRACK3DMOTA94.8Unverified
#ModelMetricClaimedVerifiedStatus
1Siam-FCAverage IOU0.66Unverified
#ModelMetricClaimedVerifiedStatus
1RT-MDNetPrecision Plot0.63Unverified