Point Tracking

Point Tracking, often referred to as Tracking any Point (TAP) involves acquiring, focusing on, and continuously tracking specific target point/points across video frames. The system identifies the target point, maintains focus, and predicts its movement, enabling smooth tracking even if the target moves unpredictably, or through occlusions. TAP has wide applications like object tracking, surveillance, and autonomous navigation.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 41–50 of 151 papers

Title	Date	Tasks	Status	Hype	Score
Deep Learning based Virtual Point Tracking for Real-Time Target-less Dynamic Displacement Measurement in Railway Applications	Jan 17, 2021	Edge DetectionLine Detection	CodeCode Available	1	5
Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer	Aug 10, 2022	3D Object TrackingAutonomous Driving	CodeCode Available	1	5
Autogenic Language Embedding for Coherent Point Tracking	Jul 30, 2024	DecoderPoint Tracking	CodeCode Available	0	5
RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation	Aug 30, 2023	Point TrackingRobot Manipulation	CodeCode Available	0	5
A Training-Free Framework for Video License Plate Tracking and Recognition with Only One-Shot	Aug 11, 2024	License Plate DetectionLicense Plate Recognition	CodeCode Available	0	5
Optimal Video Compression using Pixel Shift Tracking	Jun 28, 2024	Point TrackingVideo Compression	CodeCode Available	0	5
PIPsUS: Self-Supervised Dense Point Tracking in Ultrasound	Mar 8, 2024	Data AugmentationLandmark Tracking	CodeCode Available	0	5
Point Tracking in Surgery--The 2024 Surgical Tattoos in Infrared (STIR) Challenge	Mar 31, 2025	3D ReconstructionPoint Tracking	CodeCode Available	0	5
Multiple model estimation under perspective of random-fuzzy dual interpretation of unknown uncertainty	Apr 1, 2024	Keypoint EstimationPoint Tracking	CodeCode Available	0	5
Muscle Excitation Estimation in Biomechanical Simulation Using NAF Reinforcement Learning	Sep 17, 2018	Deep Reinforcement LearningPoint Tracking	CodeCode Available	0	5

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All datasets TAP-Vid-DAVIS PointOdyssey TAP-Vid-DAVIS-First TAP-Vid-Kinetics TAP-Vid-Kinetics-First TAP-Vid-RGB-Stacking Perception Test TAP-Vid

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	LocoTrack-B	Average Jaccard	69.4	—	Unverified
2	BootsTAPIR	Average Jaccard	66.2	—	Unverified
3	CoTracker	Average Jaccard	65.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PIPs++	Survival	50.47	—	Unverified
2	PIPs+	Survival	49.88	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LocoTrack-B	Average Jaccard	64.8	—	Unverified
2	CoTracker	Average Jaccard	62.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BootsTAPIR	Average Jaccard	61.4	—	Unverified
2	LocoTrack-B	Average Jaccard	59.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LocoTrack-B	Average Jaccard	52.3	—	Unverified
2	CoTracker	Average Jaccard	48.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BootsTAPIR	Average Jaccard	72.4	—	Unverified
2	LocoTrack-B	Average Jaccard	70.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Static Baseline	Average Jaccard	0.36	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PIPs++	MTE	4.6	—	Unverified