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 12761300 of 1966 papers

TitleStatusHype
GMOT-40: A Benchmark for Generic Multiple Object TrackingCode1
Is First Person Vision Challenging for Object Tracking?0
Siamese Tracking with Lingual Object ConstraintsCode0
Graph Attention Tracking0
Transparent Object Tracking Benchmark0
Learning Local Feature Descriptors for Multiple Object Tracking0
Online Multi-Object Tracking with delta-GLMB Filter based on Occlusion and Identity Switch Handling0
TRAT: Tracking by Attention Using Spatio-Temporal Features0
Efficient Data Association and Uncertainty Quantification for Multi-Object Tracking0
Overlapping neural representations for the position of visible and imagined objects0
Faster object tracking pipeline for real time tracking0
Online Descriptor Enhancement via Self-Labelling Triplets for Visual Data Association0
Motion Prediction on Self-driving Cars: A Review0
Uncertainty-Aware Voxel based 3D Object Detection and Tracking with von-Mises LossCode0
SMOT: Single-Shot Multi Object TrackingCode0
Multiple Trajectory Prediction with Deep Temporal and Spatial Convolutional Neural Networks0
Dynamic Resource-aware Corner Detection for Bio-inspired Vision Sensors0
Multi-object tracking with self-supervised associating network0
A Hierarchical Graph Signal Processing Approach to Inference from Spatiotemporal Signals0
Rethinking the competition between detection and ReID in Multi-Object TrackingCode1
F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking0
ApproxDet: Content and Contention-Aware Approximate Object Detection for MobilesCode1
Tracking from Patterns: Learning Corresponding Patterns in Point Clouds for 3D Object Tracking0
Multiple Pedestrians and Vehicles Tracking in Aerial Imagery: A Comprehensive Study0
Tracklets Predicting Based Adaptive Graph Tracking0
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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