mlsanityData to 14 Oct 2026

Context-PIPs: Persistent Independent Particles Demands Spatial Context Features

arXiv 2306.02000 ↗First posted 3 Jun 2023cs.CVcited by 9

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Abstract (arXiv)

We tackle the problem of Persistent Independent Particles (PIPs), also called Tracking Any Point (TAP), in videos, which specifically aims at estimating persistent long-term trajectories of query points in videos. Previous methods attempted to estimate these trajectories independently to incorporate longer image sequences, therefore, ignoring the potential benefits of incorporating spatial context features. We argue that independent video point tracking also demands spatial context features. To this end, we propose a novel framework Context-PIPs, which effectively improves point trajectory accuracy by aggregating spatial context features in videos. Context-PIPs contains two main modules: 1) a SOurse Feature Enhancement (SOFE) module, and 2) a TArget Feature Aggregation (TAFA) module. Context-PIPs significantly improves PIPs all-sided, reducing 11.4% Average Trajectory Error of Occluded Points (ATE-Occ) on CroHD and increasing 11.8% Average Percentage of Correct Keypoint (A-PCK) on TAP-Vid-Kinectics. Demos are available at https://wkbian.github.io/Projects/Context-PIPs/.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 32 of its 50 references that are in the map. First posted on arXiv 3 Jun 2023.

Builds on

32 of 50 references.

References · 32

  1. 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,968
  2. 2020RAFT: Recurrent All-Pairs Field Transforms for Optical Flowcited by 2,415
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  11. 2022Kubric: A scalable dataset generatorcited by 381
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20 more
  1. 2022TAP-Vid: A Benchmark for Tracking Any Point in a Videocited by 263
  2. 2021Learning to Estimate Hidden Motions with Global Motion Aggregationcited by 224
  3. 2022Particle Video Revisited: Tracking Through Occlusions Using Point Trajectoriescited by 217
  4. 2021COTR: Correspondence Transformer for Matching Across Imagescited by 183
  5. 2021E-RAFT: Dense Optical Flow from Event Camerascited by 152
  6. 2023FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimationcited by 114
  7. 2019Deep Video Inpaintingcited by 109
  8. 2022ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wildcited by 92
  9. 2022CRAFT: Cross-Attentional Flow Transformer for Robust Optical Flowcited by 82
  10. 2023VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimationcited by 82
  11. 2021Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspectivecited by 81
  12. 2019A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularizationcited by 76
  13. 2022SKFlow: Learning Optical Flow with Super Kernelscited by 56
  14. 2023A Dynamic Multi-Scale Voxel Flow Network for Video Predictioncited by 53
  15. 2021Tracking Pedestrian Heads in Dense Crowdcited by 42
  16. 2018A Fusion Approach for Multi-Frame Optical Flow Estimationcited by 37
  17. 2020FlowFusion: Dynamic Dense RGB-D SLAM Based on Optical Flowcited by 37
  18. 2022Learning Degradation Representations for Image Deblurringcited by 35
  19. 2023BlinkFlow: A Dataset to Push the Limits of Event-based Optical Flow Estimationcited by 33
  20. 2021VOLDOR: Visual Odometry from Log-logistic Dense Optical flow Residualscited by 17

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 5; 2025: 3; 2026: 1.

9 papers.

  1. 2025TAPIP3D: Tracking Any Point in Persistent 3D Geometrycited by 69
  2. 2024Diffusion Model-Based Video Editing: A Surveycited by 44
  3. 2025GS-DiT: Advancing Video Generation with Pseudo 4D Gaussian Fields through Efficient Dense 3D Point Trackingcited by 39
  4. 2024TAPTRv2: Attention-based Position Update Improves Tracking Any Pointcited by 18
  5. 2025L4P: Towards Unified Low-Level 4D Vision Perceptioncited by 12
  6. 2024TAPTRv3: Spatial and Temporal Context Foster Robust Tracking of Any Point in Long Videocited by 8
  7. 2024BlinkTrack: Feature Tracking over 80 FPS via Events and Imagescited by 4
  8. 2024MATE: Motion-Augmented Temporal Consistency for Event-based Point Trackingcited by 4
  9. 2026GoStop: Reinforcement Learning for Adaptive Temporal Aggregation in Event-Based Feature Trackingcited by 0