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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 1876–1900 of 1966 papers

Title	Date	Tasks	Status
Local Subspace Collaborative Tracking	Dec 1, 2015	ObjectObject Tracking	—Unverified
Exploring Causal Relationships in Visual Object Tracking	Dec 1, 2015	ObjectObject Tracking	—Unverified
Visual Tracking With Fully Convolutional Networks	Dec 1, 2015	Object TrackingVisual Tracking	—Unverified
Multiple Feature Fusion via Weighted Entropy for Visual Tracking	Dec 1, 2015	ObjectObject Tracking	—Unverified
Hierarchical Convolutional Features for Visual Tracking	Dec 1, 2015	Object RecognitionObject Tracking	—Unverified
Sliding-Window Optimization on an Ambiguity-Clearness Graph for Multi-object Tracking	Nov 28, 2015	Multi-Object TrackingObject Tracking	—Unverified
Video Tracking Using Learned Hierarchical Features	Nov 25, 2015	Domain AdaptationNetwork Embedding	—Unverified
Coreset-Based Adaptive Tracking	Nov 19, 2015	ObjectObject Tracking	—Unverified
First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks	Nov 19, 2015	ObjectObject Tracking	—Unverified
UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking	Nov 13, 2015	Multi-Object TrackingObject	—Unverified
Regional Active Contours based on Variational level sets and Machine Learning for Image Segmentation	Oct 31, 2015	BIG-bench Machine LearningImage Segmentation	—Unverified
RATM: Recurrent Attentive Tracking Model	Oct 29, 2015	modelObject Tracking	—Unverified
Visual Tracking via Nonnegative Regularization Multiple Locality Coding	Oct 5, 2015	Object TrackingVisual Tracking	—Unverified
Effective Object Tracking in Unstructured Crowd Scenes	Oct 2, 2015	ObjectObject Tracking	—Unverified
Online Object Tracking with Proposal Selection	Sep 30, 2015	ObjectObject Tracking	—Unverified
Efficient Discriminative Nonorthogonal Binary Subspace with its Application to Visual Tracking	Sep 28, 2015	feature selectionObject	—Unverified
Robust video object tracking using particle filter with likelihood based feature fusion and adaptive template updating	Sep 28, 2015	ObjectObject Tracking	—Unverified
Online Object Tracking, Learning and Parsing with And-Or Graphs	Sep 27, 2015	Object Tracking	CodeCode Available
Robust Object Tracking with a Hierarchical Ensemble Framework	Sep 23, 2015	ObjectObject Tracking	—Unverified
An Experimental Survey on Correlation Filter-based Tracking	Sep 18, 2015	Object TrackingSurvey	—Unverified
An On-line Variational Bayesian Model for Multi-Person Tracking from Cluttered Scenes	Sep 4, 2015	Multiple Object TrackingObject	—Unverified
Iterative hypothesis testing for multi-object tracking in presence of features with variable reliability	Sep 1, 2015	Multi-Object TrackingObject Tracking	—Unverified
Online Domain Adaptation for Multi-Object Tracking	Aug 4, 2015	Domain AdaptationMulti-Object Tracking	—Unverified
Online Metric-Weighted Linear Representations for Robust Visual Tracking	Jul 21, 2015	Metric LearningObject	—Unverified
Automatic tracking of protein vesicles	Jun 5, 2015	Multiple Object TrackingObject	—Unverified

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All datasets COESOT FE108 QuadTrack SeaDronesSee BIRDSAI - ICVGIP 2020 KITTI MMPTRACK Perception Test VisEvent

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	HR-CEUTrack-Large	Success Rate	65	—	Unverified
2	HR-CEUTrack-Base	Success Rate	63.2	—	Unverified
3	CEUTrack-Large	Success Rate	62.8	—	Unverified
4	CEUTrack-Base	Success Rate	62	—	Unverified
5	SiamR-CNN	Success Rate	60.9	—	Unverified
6	TransT	Success Rate	60.5	—	Unverified
7	SuperDiMP	Success Rate	60.2	—	Unverified
8	TrDiMP	Success Rate	60.1	—	Unverified
9	KeepTrack	Success Rate	59.6	—	Unverified
10	AiATrack	Success Rate	59	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HR-MonTrack-Base	Success Rate	68.5	—	Unverified
2	HR-MonTrack-Tiny	Success Rate	66.3	—	Unverified
3	Multi-modal	Success Rate	63.4	—	Unverified
4	PrDiMP	Success Rate	59	—	Unverified
5	DiMP	Success Rate	57.1	—	Unverified
6	MonTrack	Success Rate	54.9	—	Unverified
7	ATOM	Success Rate	46.5	—	Unverified
8	KYS	Success Rate	26.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OmniTrack	HOTA	23.45	—	Unverified
2	DeepSORT	HOTA	21.16	—	Unverified
3	OC-SORT	HOTA	20.83	—	Unverified
4	ByteTrack	HOTA	20.66	—	Unverified
5	TrackFormer	HOTA	19.62	—	Unverified
6	HybridSORT	HOTA	16.64	—	Unverified
7	DiffMOT	HOTA	16.4	—	Unverified
8	Bot-SORT	HOTA	15.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DiMP50	Success Rate	67.33	—	Unverified
2	PrDiMP50	Success Rate	67	—	Unverified
3	PrDiMP18	Success Rate	65.9	—	Unverified
4	DiMP18	Success Rate	64.6	—	Unverified
5	Atom	Success Rate	63.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	final	Humans	0.14	—	Unverified
2	night_fury	Humans	0.05	—	Unverified
3	Yolo based method	Humans	0.02	—	Unverified
4	final	Humans	0	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	M2-Track	mean precision	83.4	—	Unverified
2	BAT	mean precision	75.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UMMT	3DMOTA	95	—	Unverified
2	MMPTRACK	3DMOTA	94.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Siam-FC	Average IOU	0.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RT-MDNet	Precision Plot	0.63	—	Unverified