mlsanityData to 7 Oct 2026

Track4World: Feedforward World-centric Dense 3D Tracking of All Pixels

arXiv 2603.02573 ↗First posted 3 Mar 2026cs.CVcited by 10

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Abstract (arXiv)

Estimating the 3D trajectory of every pixel from a monocular video is crucial and promising for a comprehensive understanding of the 3D dynamics of videos. Recent monocular 3D tracking works demonstrate impressive performance, but are limited to either tracking sparse points on the first frame or a slow optimization-based framework for dense tracking. In this paper, we propose a feedforward model, called Track4World, enabling an efficient holistic 3D tracking of every pixel in the world-centric coordinate system. Built on the global 3D scene representation encoded by a VGGT-style ViT, Track4World applies a novel 3D correlation scheme to simultaneously estimate the pixel-wise 2D and 3D dense flow between arbitrary frame pairs. The estimated scene flow, along with the reconstructed 3D geometry, enables subsequent efficient 3D tracking of every pixel of this video. Extensive experiments on multiple benchmarks demonstrate that our approach consistently outperforms existing methods in 2D/3D flow estimation and 3D tracking, highlighting its robustness and scalability for real-world 4D reconstruction tasks.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 94 of its 109 references that are in the map. First posted on arXiv 3 Mar 2026.

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94 of 109 references.

References · 94

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2023Segment Anythingcited by 8,158
  3. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,274
  4. 2017Quo Vadis, Action Recognition? A New Model and the Kinetics Datasetcited by 3,259
  5. 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,088
  6. 2020RAFT: Recurrent All-Pairs Field Transforms for Optical Flowcited by 2,385
  7. 2023DUSt3R: Geometric 3D Vision Made Easycited by 1,526
  8. 2025VGGT: Visual Geometry Grounded Transformercited by 1,475
  9. 2015FlowNet: Learning Optical Flow with Convolutional Networkscited by 1,054
  10. 2024Grounding Image Matching in 3D with MASt3Rcited by 960
  11. 2015A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimationcited by 878
  12. 2023ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenescited by 747
38 more
  1. 2025Depth Anything 3: Recovering the Visual Space from Any Viewscited by 626
  2. 2020Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understandingcited by 593
  3. 2025Continuous 3D Perception Model with Persistent Statecited by 527
  4. 2023CoTracker: It is Better to Track Togethercited by 516
  5. 2020TartanAir: A Dataset to Push the Limits of Visual SLAMcited by 494
  6. 2021ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Datacited by 442
  7. 2024MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motioncited by 431
  8. 2024UniDepth: Universal Monocular Metric Depth Estimationcited by 375
  9. 2022Kubric: A scalable dataset generatorcited by 373
  10. 2025Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Passcited by 356
  11. 2016Virtual Worlds as Proxy for Multi-Object Tracking Analysiscited by 340
  12. 2025MapAnything: Universal Feed-Forward Metric 3D Reconstructioncited by 295
  13. 2025π3: Permutation-Equivariant Visual Geometry Learningcited by 292
  14. 2024MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervisioncited by 290
  15. 2023TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinementcited by 281
  16. 2018DeepMVS: Learning Multi-view Stereopsiscited by 277
  17. 2023PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Trackingcited by 274
  18. 2022TAP-Vid: A Benchmark for Tracking Any Point in a Videocited by 258
  19. 2025MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Detailscited by 250
  20. 2018FlowNet3D: Learning Scene Flow in 3D Point Cloudscited by 241
  21. 2024MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videoscited by 224
  22. 2024DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videoscited by 202
  23. 2020Robust Consistent Video Depth Estimationcited by 188
  24. 2022Deep Patch Visual Odometrycited by 186
  25. 2025Diffusion as Shader: 3D-aware Video Diffusion for Versatile Video Generation Controlcited by 184
  26. 2019ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting Residualscited by 180
  27. 2024SpatialTracker: Tracking Any 2D Pixels in 3D Spacecited by 178
  28. 2023Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereocited by 170
  29. 2017Playing for Benchmarkscited by 169
  30. 2024SEA-RAFT: Simple, Efficient, Accurate RAFT for Optical Flowcited by 169
  31. 2023Aria Digital Twin: A New Benchmark Dataset for Egocentric 3D Machine Perceptioncited by 166
  32. 2025ViPE: Video Pose Engine for 3D Geometric Perceptioncited by 162
  33. 2023DynamicStereo: Consistent Dynamic Depth from Stereo Videoscited by 147
  34. 2025Streaming 4D Visual Geometry Transformercited by 147
  35. 2025TTT3R: 3D Reconstruction as Test-Time Trainingcited by 122
  36. 2020RAFT-3D: Scene Flow using Rigid-Motion Embeddingscited by 121
  37. 2024BootsTAP: Bootstrapped Training for Tracking-Any-Pointcited by 115
  38. 2025Go-with-the-Flow: Motion-Controllable Video Diffusion Models Using Real-Time Warped Noisecited by 114

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Citing papers per year: 2026: 10.

10 papers.