SOTAVerified

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

Showing 2650 of 151 papers

TitleStatusHype
POMATO: Marrying Pointmap Matching with Temporal Motion for Dynamic 3D ReconstructionCode2
Fréchet Video Motion Distance: A Metric for Evaluating Motion Consistency in VideosCode2
Exploring Temporally-Aware Features for Point TrackingCode2
Decomposition Betters Tracking Everything EverywhereCode2
PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point TrackingCode2
MATCHA: Towards Matching AnythingCode2
SD-DefSLAM: Semi-Direct Monocular SLAM for Deformable and Intracorporeal ScenesCode1
PTTR: Relational 3D Point Cloud Object Tracking with TransformerCode1
Point 4D Transformer Networks for Spatio-Temporal Modeling in Point Cloud VideosCode1
Augmenting Efficient Real-time Surgical Instrument Segmentation in Video with Point Tracking and Segment AnythingCode1
Motion-prior Contrast Maximization for Dense Continuous-Time Motion EstimationCode1
Low Complexity Point Tracking of the Myocardium in 2D EchocardiographyCode1
Online Dense Point Tracking with Streaming MemoryCode1
MFT: Long-Term Tracking of Every PixelCode1
DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion ModelCode1
Deep Learning based Virtual Point Tracking for Real-Time Target-less Dynamic Displacement Measurement in Railway ApplicationsCode1
Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with TransformerCode1
Autogenic Language Embedding for Coherent Point TrackingCode0
RoboTAP: Tracking Arbitrary Points for Few-Shot Visual ImitationCode0
A Training-Free Framework for Video License Plate Tracking and Recognition with Only One-ShotCode0
Optimal Video Compression using Pixel Shift TrackingCode0
PIPsUS: Self-Supervised Dense Point Tracking in UltrasoundCode0
Point Tracking in Surgery--The 2024 Surgical Tattoos in Infrared (STIR) ChallengeCode0
Multiple model estimation under perspective of random-fuzzy dual interpretation of unknown uncertaintyCode0
Muscle Excitation Estimation in Biomechanical Simulation Using NAF Reinforcement LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LocoTrack-BAverage Jaccard69.4Unverified
2BootsTAPIRAverage Jaccard66.2Unverified
3CoTrackerAverage Jaccard65.9Unverified
#ModelMetricClaimedVerifiedStatus
1PIPs++Survival50.47Unverified
2PIPs+Survival49.88Unverified
#ModelMetricClaimedVerifiedStatus
1LocoTrack-BAverage Jaccard64.8Unverified
2CoTrackerAverage Jaccard62.2Unverified
#ModelMetricClaimedVerifiedStatus
1BootsTAPIRAverage Jaccard61.4Unverified
2LocoTrack-BAverage Jaccard59.1Unverified
#ModelMetricClaimedVerifiedStatus
1LocoTrack-BAverage Jaccard52.3Unverified
2CoTrackerAverage Jaccard48.8Unverified
#ModelMetricClaimedVerifiedStatus
1BootsTAPIRAverage Jaccard72.4Unverified
2LocoTrack-BAverage Jaccard70.8Unverified
#ModelMetricClaimedVerifiedStatus
1Static BaselineAverage Jaccard0.36Unverified
#ModelMetricClaimedVerifiedStatus
1PIPs++MTE4.6Unverified