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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 501–525 of 1966 papers

TitleStatusHype
DropTrack -- automatic droplet tracking using deep learning for microfluidic applications—0
BOTT: Box Only Transformer Tracker for 3D Object Tracking—0
Active inference body perception and action for humanoid robots—0
DroBoost: An Intelligent Score and Model Boosting Method for Drone Detection—0
An Efficient Background Term for 3D Reconstruction and Tracking With Smooth Surface Models—0
3D Multiple Object Tracking on Autonomous Driving: A Literature Review—0
DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving—0
DreamTrack: Dreaming the Future for Multimodal Visual Object Tracking—0
DOT: Dynamic Object Tracking for Visual SLAM—0
DSRRTracker: Dynamic Search Region Refinement for Attention-based Siamese Multi-Object Tracking—0
Domain Adaptive SiamRPN++ for Object Tracking in the Wild—0
Bootstrapping Labelled Dataset Construction for Cow Tracking and Behavior Analysis—0
Does Video Compression Impact Tracking Accuracy?—0
DMV: Visual Object Tracking via Part-level Dense Memory and Voting-based Retrieval—0
Boosting Online 3D Multi-Object Tracking through Camera-Radar Cross Check—0
An Approximate Dynamic Programming Framework for Occlusion-Robust Multi-Object Tracking—0
ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints—0
DL-SLOT: Dynamic Lidar SLAM and Object Tracking Based On Graph Optimization—0
A CRF-based Framework for Tracklet Inactivation in Online Multi-Object Tracking—0
Divert More Attention to Vision-Language Object Tracking—0
Divert More Attention to Vision-Language Tracking—0
An Approach for Multi-Object Tracking with Two-Stage Min-Cost Flow—0
A Continuous, Full-scope, Spatio-temporal Tracking Metric based on KL-divergence—0
Distributed Variational Bayesian Algorithms for Extended Object Tracking—0
Distributed Extended Object Tracking Using Coupled Velocity Model from WLS Perspective—0
Show:102550
← PrevPage 21 of 79Next →
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