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
Perception Test: A Diagnostic Benchmark for Multimodal Video ModelsCode2
Fréchet Video Motion Distance: A Metric for Evaluating Motion Consistency in VideosCode2
Decomposition Betters Tracking Everything EverywhereCode2
Seurat: From Moving Points to DepthCode2
PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point TrackingCode2
MATCHA: Towards Matching AnythingCode2
Augmenting Efficient Real-time Surgical Instrument Segmentation in Video with Point Tracking and Segment AnythingCode1
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
Online Dense Point Tracking with Streaming MemoryCode1
DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion ModelCode1
Low Complexity Point Tracking of the Myocardium in 2D EchocardiographyCode1
MFT: Long-Term Tracking of Every PixelCode1
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
Motion-prior Contrast Maximization for Dense Continuous-Time Motion EstimationCode1
DATAP-SfM: Dynamic-Aware Tracking Any Point for Robust Structure from Motion in the Wild0
Data-driven predictive control with improved performance using segmented trajectories0
Analysis, design, and implementation of the AFZ converter applied to photovoltaic systems0
A Unified Power-Setpoint Tracking Algorithm for Utility-Scale PV Systems with Power Reserves and Fast Frequency Response Capabilities0
Adaptive maximum power point tracking using neural networks for a photovoltaic systems according grid0
Control Barrier Function-Based Quadratic Programming for SafeOperation of Tethered UAVs0
Context-PIPs: Persistent Independent Particles Demands Spatial Context Features0
Analysis and implementation of the Buck-Boost Modified Series Forward converter applied to photovoltaic systems0
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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