Paper Citation Record · LEDGER

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking

As of 18 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 3 inbound Pith citation observations for arXiv:2512.20606.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2512.20606 v2

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T14:24:50.041031Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T00:58:40.497878Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-14T21:29:28.947667Z

Reference resolution

65 of 65 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ae34eebe-d67b-4c98-ad3d-87c153291f73 · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.389952Z

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Unavailable: canonical work link unavailable.

Observation 5a97110c-e6a4-493b-882a-64bd428aa7c7 · outbound

This paper cites Can visual foundation models achieve long-term point tracking? InEC- CVW, 2024.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Can visual foundation models achieve long-term point tracking? InEC- CVW, 2024

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.525136Z

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Observation 8a299e67-8c2c-4b0c-9b93-20dbc9923c2a · outbound

This paper cites Track-On: Transformer-based online point tracking with memory.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Track-On: Transformer-based online point tracking with memory

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.642120Z

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Observation 9c79274d-f32a-4bc0-bd03-77bc63b63698 · outbound

This paper cites DriveTrack: A benchmark for long-range point tracking in real-world videos.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking DriveTrack: A benchmark for long-range point tracking in real-world videos

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.738532Z

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Observation 31f8982a-0d7d-462d-abd0-193aedbec7ab · outbound

This paper cites Quo vadis, action recognition? a new model and the kinetics dataset.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Quo vadis, action recognition? a new model and the kinetics dataset

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.866652Z

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Observation 41c076c1-3f1e-49bd-b4cc-40e0f057c8aa · outbound

This paper cites FlowTrack: Revisiting optical flow for long- range dense tracking.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking FlowTrack: Revisiting optical flow for long- range dense tracking

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.869836Z

Source-reported events for the cited work

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Observation 92d69132-925b-4290-9660-dba18299845a · outbound

This paper cites Local all-pair correspon- dence for point tracking.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Local all-pair correspon- dence for point tracking

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.873130Z

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Observation 18776465-0a43-478c-890c-971305fd7c0f · outbound

This paper cites Seurat: From moving points to depth.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Seurat: From moving points to depth

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.875930Z

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Observation 5f4b16cb-1abf-43b0-965a-de464f7068ba · outbound

This paper cites Is this tracker on? a benchmark protocol for dynamic tracking.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Is this tracker on? a benchmark protocol for dynamic tracking

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.878748Z

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Observation 5000c9f6-0441-4d08-a7cb-d9237112dfdf · outbound

This paper cites MOSE: A new dataset for video object segmentation in complex scenes.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking MOSE: A new dataset for video object segmentation in complex scenes

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.882124Z

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Observation c5e7a2cc-7593-44df-8d47-516c683f76be · outbound

This paper cites TAP-Vid: A benchmark for track- ing any point in a video.NeurIPS, 35:13610–13626, 2022.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking TAP-Vid: A benchmark for track- ing any point in a video.NeurIPS, 35:13610–13626, 2022

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.884852Z

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Observation 10aa5af2-639b-4c7d-98d0-f6410ce05a01 · outbound

This paper cites TAPIR: Tracking any point with per-frame initialization and temporal refinement.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking TAPIR: Tracking any point with per-frame initialization and temporal refinement

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.887708Z

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Observation d1357e20-15f9-4af1-a272-c72fa200a1b2 · outbound

This paper cites BootsTAP: Bootstrapped training for tracking-any-point.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking BootsTAP: Bootstrapped training for tracking-any-point

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.890368Z

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Observation eb37bf9f-0a33-437e-b169-0555283cda41 · outbound

This paper cites Unleashing diffu- sion transformers for visual correspondence by modulating massive activations.NeurIPS, 2025.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Unleashing diffu- sion transformers for visual correspondence by modulating massive activations.NeurIPS, 2025

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.893309Z

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Observation cfbd658d-67df-49ed-a3ee-82708fcf220f · outbound

This paper cites Motion prompting: Controlling video generation with motion trajec- tories.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Motion prompting: Controlling video generation with motion trajec- tories

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.896143Z

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Observation f5e4e64c-1bb7-49bd-a16a-e114c8b72245 · outbound

This paper cites Ego4D: Around the world in 3,000 hours of egocentric video.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Ego4D: Around the world in 3,000 hours of egocentric video

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.898905Z

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Observation a45d4666-0927-4eef-bd61-7c2f54475b76 · outbound

This paper cites Fleet, Dan Gnanapra- gasam, Florian Golemo, Charles Herrmann, et al.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Fleet, Dan Gnanapra- gasam, Florian Golemo, Charles Herrmann, et al

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.901721Z

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Observation cc66a702-2cfd-4202-88c5-87ef1c24808e · outbound

This paper cites Harley, Zhaoyuan Fang, and Katerina Fragkiadaki.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Harley, Zhaoyuan Fang, and Katerina Fragkiadaki

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.904596Z

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Observation c6c2a53c-1fcf-49a9-8c96-653b55c9186e · outbound

This paper cites Harley, Yang You, Xinglong Sun, Yang Zheng, Nikhil Raghuraman, Yunqi Gu, Sheldon Liang, Wen-Hsuan Chu, Achal Dave, Pavel Tokmakov, et al.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Harley, Yang You, Xinglong Sun, Yang Zheng, Nikhil Raghuraman, Yunqi Gu, Sheldon Liang, Wen-Hsuan Chu, Achal Dave, Pavel Tokmakov, et al

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.907275Z

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Observation 10fc45cd-b166-4e24-9293-35a0a02f4c96 · outbound

This paper cites Deep residual learning for image recognition.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Deep residual learning for image recognition

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.910344Z

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Observation 4d17f473-d0fd-4549-9d89-8346b29c1789 · outbound

This paper cites Benchmarking neu- ral network robustness to common corruptions and perturba- tions.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Benchmarking neu- ral network robustness to common corruptions and perturba- tions

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.913288Z

Source-reported events for the cited work

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Observation ee303070-89f3-4c2f-a2d0-080557402d19 · outbound

This paper cites Denoising dif- fusion probabilistic models.NeurIPS, 33:6840–6851, 2020.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Denoising dif- fusion probabilistic models.NeurIPS, 33:6840–6851, 2020

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.915954Z

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Observation a5abb6db-e25b-4e2e-89de-9f787d9051ff · outbound

This paper cites LVOS: A benchmark for long-term video object segmentation.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking LVOS: A benchmark for long-term video object segmentation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.918585Z

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Observation 0895bf86-a777-4b32-b07b-535086cdfa88 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.921316Z

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Observation fcca869b-9a6d-477d-bb7a-bf0d1de32019 · outbound

This paper cites Stereo4D: Learning how things move in 3D from internet stereo videos.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Stereo4D: Learning how things move in 3D from internet stereo videos

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.923931Z

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Observation be36ee79-b4c3-44f1-9d9f-eaee40793b61 · outbound

This paper cites CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.926648Z

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Observation 8cb20428-acf5-4508-8b3b-934c185c6eef · outbound

This paper cites Co- Tracker: It is better to track together.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Co- Tracker: It is better to track together

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.933213Z

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Observation 9a20db7b-7535-4877-9d35-27a23fa7124a · outbound

This paper cites Repurpos- ing diffusion-based image generators for monocular depth estimation.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Repurpos- ing diffusion-based image generators for monocular depth estimation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.936225Z

Source-reported events for the cited work

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Observation faef7abb-83e3-4619-af08-9a67ee9e5bec · outbound

This paper cites Exploring temporally-aware features for point tracking.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Exploring temporally-aware features for point tracking

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.939023Z

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Observation 5d8e3044-ed07-440e-88fe-4ebd9d803c01 · outbound

This paper cites Learning to track any points from human motion.arXiv preprint arXiv:2507.06233, 2025.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Learning to track any points from human motion.arXiv preprint arXiv:2507.06233, 2025

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.941786Z

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Observation 701615fe-de36-4a32-b6f8-a275d82f03d0 · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.944520Z

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Observation 17495e53-6355-4b5e-ab3a-3df584ef5e43 · outbound

This paper cites Dense optical tracking: Connecting the dots.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Dense optical tracking: Connecting the dots

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.948093Z

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Observation 4ec1c034-e5ec-44f9-bce7-cf67b4d0da00 · outbound

This paper cites TAPTRv2: Attention-based position update improves tracking any point.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking TAPTRv2: Attention-based position update improves tracking any point

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.950782Z

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Observation 67820d67-fdae-44c1-9e8f-5622a5665494 · outbound

This paper cites TAPTR: Tracking any point with transformers as detection.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking TAPTR: Tracking any point with transformers as detection

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.953483Z

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Observation 59a77615-d0e9-411c-9ab2-9d08d00fcc08 · outbound

This paper cites SD4Match: Learning to prompt stable diffu- sion model for semantic matching.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking SD4Match: Learning to prompt stable diffu- sion model for semantic matching

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.956326Z

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Observation c0bbf535-9216-4c07-8dea-6120b2872110 · outbound

This paper cites Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.959310Z

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Observation 7edf6d9b-7d02-4684-bea1-be667425451e · outbound

This paper cites TSM: Temporal shift module for efficient video understanding.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking TSM: Temporal shift module for efficient video understanding

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.962984Z

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Observation 916a207d-0708-488c-abd7-1a616732e4c5 · outbound

This paper cites Flow Matching for Generative Modeling.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Flow Matching for Generative Modeling

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.965791Z

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Observation 5470f779-d45d-474b-a5cd-7888123a85c0 · outbound

This paper cites Mind the Gap: Aligning Vision Foundation Models to Image Feature Matching.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Mind the Gap: Aligning Vision Foundation Models to Image Feature Matching

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.968980Z

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Observation df19a93e-ca3d-4c67-a02b-d07bcc60a382 · outbound

This paper cites Diffusion hyperfeatures: Search- ing through time and space for semantic correspondence.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Diffusion hyperfeatures: Search- ing through time and space for semantic correspondence

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.971914Z

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Observation 76008ce0-efd5-498c-82a1-4f3b4bba696a · outbound

This paper cites Not all diffusion model activations have been evaluated as discriminative features.NeurIPS, 37: 55141–55177, 2024.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Not all diffusion model activations have been evaluated as discriminative features.NeurIPS, 37: 55141–55177, 2024

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.974936Z

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Observation 9404ce03-0556-430d-b0ae-219d791c7cdf · outbound

This paper cites DreamMatcher: Ap- pearance matching self-attention for semantically-consistent text-to-image personalization.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking DreamMatcher: Ap- pearance matching self-attention for semantically-consistent text-to-image personalization

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.977631Z

Source-reported events for the cited work

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Observation 9dee5f80-4e64-41e6-b4ff-4246cae5dd14 · outbound

This paper cites Diffusion model for dense matching.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Diffusion model for dense matching

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.980553Z

Source-reported events for the cited work

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Observation 7f537e2d-2b3e-4356-ad07-70a33707cd0e · outbound

This paper cites Emergent tem- poral correspondences from video diffusion transformers.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Emergent tem- poral correspondences from video diffusion transformers

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.983741Z

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Unavailable: canonical work link unavailable.

Observation 23e5a106-6d3a-4d89-a032-6c78b0e04696 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking DINOv2: Learning Robust Visual Features without Supervision

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.986517Z

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Observation 8f42bb26-8114-4a08-8a87-12df9908ca52 · outbound

This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking The 2017 DAVIS Challenge on Video Object Segmentation

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.989545Z

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Observation a3dba75d-942e-45c4-b63a-d832f13949ee · outbound

This paper cites TAPTRv3: Spatial and temporal context foster robust tracking of any point in long video.arXiv preprint arXiv:2411.18671, 2024.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking TAPTRv3: Spatial and temporal context foster robust tracking of any point in long video.arXiv preprint arXiv:2411.18671, 2024

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.992653Z

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Observation 9701f532-b481-454a-8c5a-4a3cbba5d411 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking High-resolution image syn- thesis with latent diffusion models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.995491Z

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Observation 460e08e3-00e7-4c93-87b8-5d62e9f5d3f1 · outbound

This paper cites Particle video: Long-range mo- tion estimation using point trajectories.IJCV, 80(1):72–91,.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Particle video: Long-range mo- tion estimation using point trajectories.IJCV, 80(1):72–91,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.998411Z

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Observation 49177057-4adf-4cc4-ad48-879945916bd6 · outbound

This paper cites DINOv3.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking DINOv3

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.001185Z

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Observation 44cfb36c-6f29-4d2e-9e25-9e1a09ffd733 · outbound

This paper cites CleanDIFT: Diffusion features without noise.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking CleanDIFT: Diffusion features without noise

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.004272Z

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Observation 43b7c304-3c1c-42d4-8d37-1426903e83de · outbound

This paper cites Emergent correspondence from image diffusion.NeurIPS, 36:1363–1389, 2023.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Emergent correspondence from image diffusion.NeurIPS, 36:1363–1389, 2023

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.007045Z

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Observation 991b3bd0-e8c6-4b53-afc3-7bbf54373352 · outbound

This paper cites DINO-Tracker: Taming DINO for self-supervised point tracking in a single video.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking DINO-Tracker: Taming DINO for self-supervised point tracking in a single video

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.010092Z

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Observation 6f830326-7f3d-417e-9c2d-1ca771694829 · outbound

This paper cites RoboTAP: Tracking arbitrary points for few-shot visual imitation.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking RoboTAP: Tracking arbitrary points for few-shot visual imitation

Reference 54

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Observation 801ee485-e8ce-4edb-89fa-d0bd8e743fea · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Wan: Open and Advanced Large-Scale Video Generative Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.015846Z

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Observation 03ae073a-3751-4d75-99e1-b590b0f7799f · outbound

This paper cites Tracking everything everywhere all at once.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Tracking everything everywhere all at once

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.018716Z

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Observation 966a07cb-03ca-4688-8641-611b8c230efe · outbound

This paper cites Shape of motion: 4D reconstruc- tion from a single video.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Shape of motion: 4D reconstruc- tion from a single video

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.021424Z

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Observation 77e3d0d8-03ff-4d9b-b1e4-6ee20146ad36 · outbound

This paper cites SpatialTracker: Tracking any 2D pixels in 3D space.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking SpatialTracker: Tracking any 2D pixels in 3D space

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.024050Z

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Observation eccbeb07-636b-45fa-8020-aa93dee1fc27 · outbound

This paper cites Open-vocabulary panop- tic segmentation with text-to-image diffusion models.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Open-vocabulary panop- tic segmentation with text-to-image diffusion models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.026992Z

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Observation 12f5182a-f5c2-4439-80ad-ab28c4c246ea · outbound

This paper cites MATCHA: Towards matching anything.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking MATCHA: Towards matching anything

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.029730Z

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Observation 04e8d77a-e119-45a5-814c-b95acd252a90 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.032484Z

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Observation 2cd55ece-a74d-4998-acbe-2c683c3ff317 · outbound

This paper cites A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence.NeurIPS, 36: 45533–45547, 2023.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence.NeurIPS, 36: 45533–45547, 2023

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.035528Z

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Observation 8c64c5c0-3d1b-44de-aa42-ffd07badfa0d · outbound

This paper cites Telling left from right: Identifying geometry-aware semantic corre- spondence.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Telling left from right: Identifying geometry-aware semantic corre- spondence

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.038330Z

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Observation 1475eefc-0c7e-437f-93c7-e50e8a267a6b · outbound

This paper cites TAPNext: Tracking any point (TAP) as next token prediction.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking TAPNext: Tracking any point (TAP) as next token prediction

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:50.041031Z

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Observation 0f0ffd0d-e3e1-453e-9570-00eb643378d1 · outbound

This paper cites an unresolved cited work.

Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking Unresolved cited work

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T14:24:49.929912Z

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Pith citing papers

Observation 1ad67764-8a1e-415c-9f5f-4fa44f865a6f · inbound

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TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-06-30T03:17:26.209732Z

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Observation b16e9fe9-2d55-4840-bab2-3a2aed90ce51 · inbound

Awakening Diffusion Transformers: Eliciting Stronger Generation and Understanding via Massive Activation Modulation cites this paper.

Awakening Diffusion Transformers: Eliciting Stronger Generation and Understanding via Massive Activation Modulation Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-12T05:46:45.293902Z

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Observation 78783360-127a-4b11-aeff-7ca67c429118 · inbound

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DreamTraj: Generating 6-DoF Object Trajectories by Reading Unrendered Video Diffusion Latents Probing and Leveraging Video Diffusion Transformer Features for Robust Point Tracking

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T00:58:40.497878Z

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